Indicating a predicted angle of departure

ABSTRACT

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first network node may receive a signal. The first network node may transmit an angle of departure (AoD) report that indicates at least one predicted AoD associated with a dominant channel cluster, wherein the at least one predicted AoD is based at least in part on the signal. Numerous other aspects are described.

INTRODUCTION

Aspects of the present disclosure generally relate to wirelesscommunication and to techniques and apparatuses for analog beamformingfor millimeter wave communications.

Wireless communication systems are widely deployed to provide varioustelecommunication services such as telephony, video, data, messaging,and broadcasts. Typical wireless communication systems may employmultiple-access technologies capable of supporting communication withmultiple users by sharing available system resources (e.g., bandwidth,transmit power, or the like). Examples of such multiple-accesstechnologies include code division multiple access (CDMA) systems, timedivision multiple access (TDMA) systems, frequency division multipleaccess (FDMA) systems, orthogonal frequency division multiple access(OFDMA) systems, single-carrier frequency division multiple access(SC-FDMA) systems, time division synchronous code division multipleaccess (TD-SCDMA) systems, and Long Term Evolution (LTE).LTE/LTE-Advanced is a set of enhancements to the Universal MobileTelecommunications System (UMTS) mobile standard promulgated by theThird Generation Partnership Project (3GPP).

A wireless network may include one or more base stations that supportcommunication for a user equipment (UE) or multiple UEs. A UE maycommunicate with a base station via downlink communications and uplinkcommunications. “Downlink” (or “DL”) refers to a communication link fromthe base station to the UE, and “uplink” (or “UL”) refers to acommunication link from the UE to the base station.

The above multiple access technologies have been adopted in varioustelecommunication standards to provide a common protocol that enablesdifferent UEs to communicate on a municipal, national, regional, and/orglobal level. New Radio (NR), which may be referred to as 5G, is a setof enhancements to the LTE mobile standard promulgated by the 3GPP. NRis designed to better support mobile broadband internet access byimproving spectral efficiency, lowering costs, improving services,making use of new spectrum, and better integrating with other openstandards using orthogonal frequency division multiplexing (OFDM) with acyclic prefix (CP) (CP-OFDM) on the downlink, using CP-OFDM and/orsingle-carrier frequency division multiplexing (SC-FDM) (also known asdiscrete Fourier transform spread OFDM (DFT-s-OFDM)) on the uplink, aswell as supporting beamforming, multiple-input multiple-output (MIMO)antenna technology, and carrier aggregation. As the demand for mobilebroadband access continues to increase, further improvements in LTE, NR,and other radio access technologies remain useful.

SUMMARY

Some aspects described herein relate to a first network node forwireless communication. The first network node may include a memory andone or more processors coupled to the memory. The one or more processorsmay be configured to receive a signal. The one or more processors may beconfigured to transmit an angle of departure (AoD) report that indicatesat least one predicted AoD associated with a dominant channel cluster.The at least one predicted AoD may be based at least in part on thesignal.

Some aspects described herein relate to a first network node forwireless communication. The first network node may include a memory andone or more processors coupled to the memory. The one or more processorsmay be configured to cause the first network node to receive a signal.The one or more processors may be configured to cause the first networknode to transmit an angle of departure (AoD) report that indicates atleast one predicted AoD associated with a dominant channel cluster. Theat least one predicted AoD may be based at least in part on the signal.

Some aspects described herein relate to a first network node forwireless communication. The first network node may include a memory andone or more processors coupled to the memory. The one or more processorsmay be configured to transmit a signal. The one or more processors maybe configured to receive an AoD report that indicates at least onepredicted AoD associated with a dominant channel cluster. The at leastone predicted AoD may be based at least in part on the signal.

Some aspects described herein relate to a first network node forwireless communication. The first network node may include a memory andone or more processors coupled to the memory. The one or more processorsmay be configured to cause the first network node to transmit a signal.The one or more processors may be configured to cause the first networknode to receive an AoD report that indicates at least one predicted AoDassociated with a dominant channel cluster. The at least one predictedAoD may be based at least in part on the signal.

Some aspects described herein relate to a method of wirelesscommunication performed by a first network node. The method may includereceiving a signal. The method may include transmitting an AoD reportthat indicates at least one predicted AoD associated with a dominantchannel cluster. The at least one predicted AoD may be based at least inpart on the signal.

Some aspects described herein relate to a method of wirelesscommunication performed by a first network node. The method may includetransmitting a signal. The method may include receiving an AoD reportthat indicates at least one predicted AoD associated with a dominantchannel cluster. The at least one predicted AoD may be based at least inpart on the signal.

Some aspects described herein relate to a non-transitorycomputer-readable medium that stores a set of instructions for wirelesscommunication by a first network node. The set of instructions, whenexecuted by one or more processors of the first network node, may causethe first network node to receive a signal. The set of instructions,when executed by one or more processors of the first network node, maycause the first network node to transmit an AoD report that indicates atleast one predicted AoD associated with a dominant channel cluster. Theat least one predicted AoD may be based at least in part on the signal.

Some aspects described herein relate to a non-transitorycomputer-readable medium that stores a set of instructions for wirelesscommunication by a first network node. The set of instructions, whenexecuted by one or more processors of the first network node, may causethe first network node to transmit a signal. The set of instructions,when executed by one or more processors of the first network node, maycause the first network node to receive an AoD report that indicates atleast one predicted AoD associated with a dominant channel cluster. Theat least one predicted AoD may be based at least in part on the signal.

Some aspects described herein relate to an apparatus for wirelesscommunication. The apparatus may include means for receiving a signal.The apparatus may include means for transmitting an AoD report thatindicates at least one predicted AoD associated with a dominant channelcluster. The at least one predicted AoD may be based at least in part onthe signal.

Some aspects described herein relate to an apparatus for wirelesscommunication. The apparatus may include means for transmitting asignal. The apparatus may include means for receiving an AoD report thatindicates at least one predicted AoD associated with a dominant channelcluster. The at least one predicted AoD may be based at least in part onthe signal.

Aspects generally include a method, apparatus, system, computer programproduct, non-transitory computer-readable medium, user equipment, basestation, wireless communication device, and/or processing system assubstantially described with reference to and as illustrated by thedrawings and specification.

The foregoing has outlined rather broadly the features and technicaladvantages of examples according to the disclosure in order that thedetailed description that follows may be better understood. Additionalfeatures and advantages will be described hereinafter. The conceptionand specific examples disclosed may be readily utilized as a basis formodifying or designing other structures for carrying out the samepurposes of the present disclosure. Such equivalent constructions do notdepart from the scope of the appended claims. Characteristics of theconcepts disclosed herein, both their organization and method ofoperation, together with associated advantages will be better understoodfrom the following description when considered in connection with theaccompanying figures. Each of the figures is provided for the purpose ofillustration and description, and not as a definition of the limits ofthe claims.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the above-recited features of the present disclosure can beunderstood in detail, a more particular description, briefly summarizedabove, may be had by reference to aspects, some of which are illustratedin the appended drawings. It is to be noted, however, that the appendeddrawings illustrate only certain typical aspects of this disclosure andare therefore not to be considered limiting of its scope, for thedescription may admit to other equally effective aspects. The samereference numbers in different drawings may identify the same or similarelements.

FIG. 1 is a diagram illustrating an example of a wireless network, inaccordance with the present disclosure.

FIG. 2 is a diagram illustrating an example of a base station incommunication with a user equipment (UE) in a wireless network, inaccordance with the present disclosure.

FIG. 3 is a diagram illustrating an example disaggregated base stationarchitecture, in accordance with the present disclosure.

FIG. 4A is a diagram illustrating an example of analog beamforming formillimeter wave communications, in accordance with the presentdisclosure.

FIG. 4B is a diagram illustrating an example of analog beamforming formillimeter wave communications, in accordance with the presentdisclosure.

FIG. 4C is a diagram illustrating an example of analog beamforming formillimeter wave communications, showing an angle of departure (AoD) andan angle of arrival (AoA), in accordance with the present disclosure.

FIG. 5 is a diagram illustrating an example associated with predictingangles of departure (AoDs), in accordance with the present disclosure.

FIG. 6A is a diagram illustrating an example associated with using asparse recovery operation to predict an AoD, in accordance with thepresent disclosure.

FIG. 6B is a diagram illustrating an example associated with using asparse recovery operation to predict an AoD, in accordance with thepresent disclosure.

FIG. 6C is a diagram illustrating an example of analog beamforming formillimeter wave communications, showing an angle of departure (AoD) andan angle of arrival (AoA), in accordance with the present disclosure.

FIG. 7 is a flow chart illustrating an example of an orthogonal matchingpursuit (OMP) procedure that may be used to determine a predicted AoD,in accordance with the present disclosure.

FIG. 8A is a diagram illustrating an example associated with beamselection, in accordance with the present disclosure.

FIG. 8B is a diagram illustrating an example associated with beamselection, in accordance with the present disclosure.

FIG. 9 is a diagram illustrating an example process associated withindicating a predicted AoD, in accordance with the present disclosure.

FIG. 10 is a diagram illustrating an example process associated withindicating a predicted AoD, in accordance with the present disclosure.

FIG. 11 is a diagram of an example apparatus for wireless communication,in accordance with the present disclosure.

FIG. 12 is a diagram illustrating an example of a hardwareimplementation for an apparatus employing a processing system, inaccordance with the present disclosure.

FIG. 13 is a diagram illustrating an example implementation of code andcircuitry for an apparatus, in accordance with the present disclosure.

DETAILED DESCRIPTION

To support millimeter wave (mmW) communications, network nodes may beoutfitted with antenna arrays having the capability to generate beamsand perform beamforming. “Beam” may refer to a directional transmissionsuch as a wireless signal that is transmitted in a direction of areceiver network node. A beam may include a directional signal, adirection associated with a signal, a set of directional resourcesassociated with a signal (e.g., angle of arrival, horizontal direction,vertical direction), and/or a set of parameters that indicate one ormore aspects of a directional signal, a direction associated with asignal, and/or a set of directional resources associated with a signal.

Beamforming includes generation of a beam using multiple signals ondifferent antenna elements, where one or more, or all, of the multiplesignals are shifted in phase relative to each other. The formed beam maycarry physical or higher layer reference signals or information. As eachsignal of the multiple signals is radiated from a respective antennaelement, the radiated signals interact, interfere (constructive anddestructive interference), and amplify each other to form a resultingbeam. The shape (such as the amplitude, width, and/or presence of sidelobes) and the direction (such as an angle of the beam relative to asurface of an antenna array) can be dynamically controlled by modifyingthe phase shifts or phase offsets of the multiple signals relative toeach other.

Analog beamforming is beamforming performed by analog circuit componentsthat branch an analog signal, which has completed digital signalprocessing, into a plurality of paths, and forms a beam by setting aphase shift (PS) and a power amplifier (PA) in each path. Unlike analogbeamforming, digital beamforming uses baseband processing to form beamsat the digital stage to maximize diversity and multiplexing gain in aMIMO environment. Hybrid beamforming is beamforming that includes bothan analog beamforming component and a digital beamforming component.

In some cases, a receiver network node and a transmitter network nodecan perform a beam management procedure in which the receiver networknode and the transmitter network node identify beam pairs to be used forcommunication. The beam management procedure can include the transmitternetwork node performing beam sweeping over multiple transmit (Tx) beamsand/or the receiver network node performing receive (Rx) beam sweepingover multiple Rx beams. The beam management procedure can enable thereceiver network node to measure CSI-RSs on different transmit beamsusing different receive beams to support selection of transmitternetwork node transmit beams/receiver network node receive beam(s) beampair(s). The beam pairs may be selected, for example, based onmeasurements of reference signal received power (RSRP).

In performing the beam management procedures described above, thereceive and transmit beams are selected from respective beamformingcodebooks. A beamforming codebook includes a set of possible beamformingparameters that may be used to beamform a signal. The beamformingparameters may include, for example, phase shifts and/or amplitudecoefficients and often are represented using beamforming weights. Insome cases, the transmitter network node selects beams from atransmitter network node beamforming codebook and the receiver networknode selects beams from a receiver network node beamforming codebook.However, in one example, the beamforming codebooks are not customized tothe specific channel, as they are pre-defined codebooks configured tofacilitate generation of pre-defined beams.

In some cases, a channel path of a channel cluster may facilitate ahigher quality signal transmission and reception than any of the beamsin a beamforming codebook. A channel cluster refers to a set of anglesthat includes an angle of departure (AoD) and an angle of arrival (AoA).The channel path of a channel cluster may refer to one or moredirections associated with a spatial characteristic of the channel. Forexample, the channel path of the channel cluster may refer to the one ormore directions corresponding to the AoA and/or the AoD. An AoA includesan azimuth angle and an elevation angle (sometimes referred to as azenith angle). Similarly, an AoD includes an azimuth angle and anelevation angle (zenith angle).

Although an azimuth angle of arrival is sometimes denoted as “AoA” and azenith angle of arrival is sometimes denoted as “ZoA,” the term “AoA” inthe present disclosure means “angle of arrival” and is intended to referto one or more aspects of an angle of arrival such as, for example, anazimuth angle of arrival, a zenith angle of arrival, or a combination ofthe azimuth angle of arrival and the zenith angle of arrival. Tofacilitate clarity of the description, “azimuth angle of arrival” isdenoted herein as “AaoA” and “zenith angle of arrival” is denoted hereinas “AzoA.” Similarly, although a zenith angle of departure is sometimesdenoted as “AoD” and a zenith angle of departure is sometimes denoted as“ZoD,” the term “AoD” in the present disclosure means “angle ofdeparture” and is intended to refer to one or more aspects of an angleof departure such as, for example, an azimuth angle of departure, azenith angle of departure, or the combination of the azimuth angle ofdeparture and the zenith angle of departure. To facilitate clarity ofthe description, “azimuth angle of departure” is denoted herein as“AaoD” and “zenith angle of departure” is denoted herein as “AzoD.”

In some cases, an AoD of a dominant channel cluster (e.g., a channelcluster having a highest RSRP) might facilitate a better communicationchannel than any of the beams indicated in the beamforming codebooks.Thus, use of a non-codebook beam pair may result in an improvedcommunication channel in comparison to a communication channelassociated only with beamforming codebooks. To use a beam that is notindicated in a beamforming codebook, a receiver network node shoulddetermine an estimate of the channel so that a direction associated witha dominant channel cluster can be extracted. In some cases, determiningan estimate of a channel is done by beam sweeping over an entireoversampled beamforming codebook (a codebook that is oversampled in thefrequency domain). However, sweeping over an entire oversampled codebookfor each channel estimate can generate unnecessary overhead and resultin power consumption, as an oversampled codebook often indicates a largenumber of beams.

Some aspects of the techniques and apparatuses described herein mayfacilitate predicting, at a receiver network node, at least one AoD andindicating the at least one AoD to a transmitter network node. Thetransmitter network node may use the indicated AoD to determine whetherto use a codebook beam or a non-codebook beam for beamforming acommunication between the transmitter network node and the receivernetwork node. For example, in some aspects, a receiver network node mayuse observations about analog beamformed channels to determine a channelestimate of the underlying channel. The estimate of the underlyingchannel may be used to predict the at least one AoD.

In some aspects, instead of beam sweeping over an entire oversampledbeamforming codebook to estimate the channel, a receiver network nodemay use only codebook beams in connection with a sparse recoveryoperation to estimate the channel. A sparse recovery procedure is analgorithmic procedure that facilitates a lower dimension observation ofhigher dimension variables. For example, in some cases, a sparserecovery procedure can be used when a high dimension variable (e.g., avariable with a large number of features such angular features of achannel) is sparse. In some aspects, for example, it has been observedthat, in the delay tap domain, a mmW channel is sparse because thechannel includes only a small number (e.g., two or three) of dominantchannel clusters. The delay tap domain refers to a time domain definedaccording to a series of delay taps (e.g., measurement points),separated by a delay, r, along a delay line associated with the channel.In the delay tap domain, the dh delay tap of the channel represents achannel cluster and is a sum of the delay taps, each of which may berepresented by a channel path. Thus, the receiver network node may usethe sparse recovery procedure to estimate a mmW channel based on arelatively small set of measurements. Because the receiver network nodedoes not have to sweep over the over-sampled codebook, some aspects mayfacilitate overhead reduction and power savings at the receiver networknode, while improving throughput.

In this way, some aspects of the present disclosure may facilitatecommunication using a better angular resolution for AoA(s) and AoD(s) atthe transmitter network node and the receiver network node. In someaspects, the at least one predicted AoD may enable the transmitternetwork node to generate a custom transmission beam and/or the receivernetwork node to generate a custom reception beam in the direction of thestrongest channel cluster. Using one or more of these custom beams mayimprove spectral efficiency. Improved angular resolution and spectralefficiency may facilitate more efficient communications with higherthroughput, thereby resulting in a positive impact on networkperformance.

Various aspects of the disclosure are described more fully hereinafterwith reference to the accompanying drawings. This disclosure may,however, be embodied in many different forms and should not be construedas limited to any specific structure or function presented throughoutthis disclosure. Rather, these aspects are provided so that thisdisclosure will be thorough and complete, and will fully convey thescope of the disclosure to those skilled in the art. One skilled in theart should appreciate that the scope of the disclosure is intended tocover any aspect of the disclosure disclosed herein, whether implementedindependently of or combined with any other aspect of the disclosure.For example, an apparatus may be implemented, or a method may bepracticed, using any number of the aspects set forth herein. Inaddition, the scope of the disclosure is intended to cover such anapparatus or method which is practiced using other structure,functionality, or structure and functionality in addition to or otherthan the various aspects of the disclosure set forth herein. It shouldbe understood that any aspect of the disclosure disclosed herein may beembodied by one or more elements of a claim.

Aspects and examples generally include a method, apparatus, networknode, system, computer program product, non-transitory computer-readablemedium, user equipment, base station, wireless communication device,and/or processing system as described or substantially described hereinwith reference to and as illustrated by the drawings and specification.

This disclosure may be readily utilized as a basis for modifying ordesigning other structures for carrying out the same purposes of thepresent disclosure. Such equivalent constructions do not depart from thescope of the appended claims. Characteristics of the concepts disclosedherein, both their organization and method of operation, together withassociated advantages, are better understood from the followingdescription when considered in connection with the accompanying figures.Each of the figures is provided for the purposes of illustration anddescription, and not as a definition of the limits of the claims.

While aspects are described in the present disclosure by illustration tosome examples, such aspects may be implemented in many differentarrangements and scenarios. Techniques described herein may beimplemented using different platform types, devices, systems, shapes,sizes, and/or packaging arrangements. For example, some aspects may beimplemented via integrated chip embodiments or othernon-module-component-based devices (e.g., end-user devices, vehicles,communication devices, computing devices, industrial equipment,retail/purchasing devices, medical devices, and/or artificialintelligence devices). Aspects may be implemented in chip-levelcomponents, modular components, non-modular components, non-chip-levelcomponents, device-level components, and/or system-level components.Devices incorporating described aspects and features may includeadditional components and features for implementation and practice ofclaimed and described aspects. For example, transmission and receptionof wireless signals may include one or more components for analog anddigital purposes (e.g., hardware components including antennas, radiofrequency (RF) chains, power amplifiers, modulators, buffers,processors, interleavers, adders, and/or summers). Aspects describedherein may be practiced in a wide variety of devices, components,systems, distributed arrangements, and/or end-user devices of varyingsize, shape, and constitution.

Several aspects of telecommunication systems will now be presented withreference to various apparatuses and techniques. These apparatuses andtechniques will be described in the following detailed description andillustrated in the accompanying drawings by various blocks, modules,components, circuits, steps, processes, algorithms, or the like(collectively referred to as “elements”). These elements may beimplemented using hardware, software, or combinations thereof. Whethersuch elements are implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem.

A telecommunication system may include, for example, a radio accessnetwork (RAN) that utilizes one or more aspects of one or more radioaccess technologies (RATs), as described herein. For example, in somecases, a RAN may include an open RAN (O-RAN), a RAN specified in awireless communication standard such as a standard produced by the ThirdGeneration Partnership Project (3GPP), and/or any other RAN or accesstechnology that may facilitate interactions between one or more networknodes via a communication network that includes wireless communications.

As described herein, a network node, which may be referred to as a“node,” a “network node,” or a “wireless node,” may be a base station(e.g., base station 110), a UE (e.g., UE 120), a relay device, a networkcontroller, an apparatus, a device, a computing system, one or morecomponents of any of these, and/or another processing entity configuredto perform one or more aspects of the techniques described herein. Anetwork node may be, or include, hardware, software, or a combination ofhardware and software. As an example, a network node may be a UE. Asanother example, a network node may be a base station. A network nodemay be an aggregated base station and/or one or more components of adisaggregated base station. As an example, a first network node may beconfigured to communicate with a second network node or a third networknode. The adjectives “first,” “second,” “third,” and so on are used forcontextual distinction between two or more of the modified noun inconnection with a discussion and are not meant to be absolute modifiersthat apply only to a certain respective node throughout the entiredocument. For example, a network node may be referred to as a “firstnetwork node” in connection with one discussion and may be referred toas a “second network node” in connection with another discussion, orvice versa. Reference to a UE, base station, apparatus, device,computing system, or the like may include disclosure of the UE, basestation, apparatus, device, computing system, or the like being anetwork node. For example, disclosure that a UE is configured to receiveinformation from a base station also discloses that a first network nodeis configured to receive information from a second network node.Consistent with this disclosure, once a specific example is broadened inaccordance with this disclosure (e.g., a UE is configured to receiveinformation from a base station also discloses that a first network nodeis configured to receive information from a second network node), thebroader example of the narrower example may be interpreted in thereverse, but in a broad open-ended way. In the example above where a UEbeing configured to receive information from a base station alsodiscloses a first network node being configured to receive informationfrom a second network node, “first network node” may refer to a firstUE, a first base station, a first apparatus, a first device, a firstcomputing system, a first one or more components, a first processingentity, or the like configured to receive the information from thesecond network; and “second network node” may refer to a second UE, asecond base station, a second apparatus, a second device, a secondcomputing system, a second one or more components, a second processingentity, or the like.

In some aspects, the term “receive” and its conjugates (e.g.,“receiving” and/or “received,” among other examples) may bealternatively referred to as “obtain” or its respective conjugates(e.g., “obtaining” and/or “obtained,” among other examples). Similarly,the term “transmit” and its conjugates (e.g., “transmitting” and/or“transmitted,” among other examples) may be alternatively referred to as“provide” or its respective conjugates (e.g., “providing” and/or“provided,” among other examples), “generate” or its respectiveconjugates (e.g., “generating” and/or “generated,” among otherexamples), and/or “output” or its respective conjugates (e.g.,“outputting” and/or “outputted,” among other examples.

While aspects may be described herein using terminology commonlyassociated with a 5G or New Radio (NR) radio access technology (RAT),aspects of the present disclosure can be applied to other RATs, such asa 3G RAT, a 4G RAT, and/or a RAT subsequent to 5G (e.g., 6G).

FIG. 1 is a diagram illustrating an example of a wireless network 100,in accordance with the present disclosure. The wireless network 100 maybe or may include elements of a 5G (e.g., NR) network and/or a 4G (e.g.,Long Term Evolution (LTE)) network, among other examples. The wirelessnetwork 100 may include one or more base stations 110 (shown as a BS 110a, a BS 110 b, a BS 110 c, and a BS 110 d), a user equipment (UE) 120 ormultiple UEs 120 (shown as a UE 120 a, a UE 120 b, a UE 120 c, a UE 120d, and a UE 120 e), and/or other network entities. A base station 110 isan entity that communicates with UEs 120. A base station 110 (sometimesreferred to as a BS) may include, for example, an NR base station, anLTE base station, a Node B, an eNB (e.g., in 4G), a gNB (e.g., in 5G),an access point, and/or a transmission reception point (TRP). Each basestation 110 may provide communication coverage for a particulargeographic area. In the Third Generation Partnership Project (3GPP), theterm “cell” can refer to a coverage area of a base station 110 and/or abase station subsystem serving this coverage area, depending on thecontext in which the term is used.

A base station 110 may provide communication coverage for a macro cell,a pico cell, a femto cell, and/or another type of cell. A macro cell maycover a relatively large geographic area (e.g., several kilometers inradius) and may allow unrestricted access by UEs 120 with servicesubscriptions. A pico cell may cover a relatively small geographic areaand may allow unrestricted access by UEs 120 with service subscription.A femto cell may cover a relatively small geographic area (e.g., a home)and may allow restricted access by UEs 120 having association with thefemto cell (e.g., UEs 120 in a closed subscriber group (CSG)). A basestation 110 for a macro cell may be referred to as a macro base station.A base station 110 for a pico cell may be referred to as a pico basestation. A base station 110 for a femto cell may be referred to as afemto base station or an in-home base station. In the example shown inFIG. 1 , the BS 110 a may be a macro base station for a macro cell 102a, the BS 110 b may be a pico base station for a pico cell 102 b, andthe BS 110 c may be a femto base station for a femto cell 102 c. A basestation may support one or multiple (e.g., three) cells.

In some examples, a cell may not necessarily be stationary, and thegeographic area of the cell may move according to the location of a basestation 110 that is mobile (e.g., a mobile base station). In someexamples, the base stations 110 may be interconnected to one anotherand/or to one or more other base stations 110 or network nodes (notshown) in the wireless network 100 through various types of backhaulinterfaces, such as a direct physical connection or a virtual network,using any suitable transport network.

The wireless network 100 may include one or more relay stations. A relaystation is an entity that can receive a transmission of data from anupstream station (e.g., a base station 110 or a UE 120) and send atransmission of the data to a downstream station (e.g., a UE 120 or abase station 110). A relay station may be a UE 120 that can relaytransmissions for other UEs 120. In the example shown in FIG. 1 , the BS110 d (e.g., a relay base station) may communicate with the BS 110 a(e.g., a macro base station) and the UE 120 d in order to facilitatecommunication between the BS 110 a and the UE 120 d. A base station 110that relays communications may be referred to as a relay station, arelay base station, a relay, or the like.

In some aspects, the wireless network 100 may include one or morenon-terrestrial network (NTN) deployments in which a non-terrestrialwireless communication device may include a UE (referred to herein,interchangeably, as a “non-terrestrial UE”), a BS (referred to herein,interchangeably, as a “non-terrestrial BS” and “non-terrestrial basestation”), a relay station (referred to herein, interchangeably, as a“non-terrestrial relay station”), and/or the like. As used herein, “NTN”may refer to a network for which access is facilitated by anon-terrestrial UE, non-terrestrial BS, a non-terrestrial relay station,and/or the like.

The wireless network 100 may include any number of non-terrestrialwireless communication devices. A non-terrestrial wireless communicationdevice may include a satellite, a manned aircraft system, an unmannedaircraft system (UAS) platform, and/or the like. A satellite may includea low-earth orbit (LEO) satellite, a medium-earth orbit (MEO) satellite,a geostationary earth orbit (GEO) satellite, a high elliptical orbit(HEO) satellite, and/or the like. A manned aircraft system may includean airplane, helicopter, a dirigible, and/or the like. A UAS platformmay include a high-altitude platform station (HAPS), and may include aballoon, a dirigible, an airplane, and/or the like. A non-terrestrialwireless communication device may be part of an NTN that is separatefrom the wireless network 100. Alternatively, an NTN may be part of thewireless network 100. Satellites may communicate directly and/orindirectly with other entities in wireless network 100 using satellitecommunication. The other entities may include UEs (e.g., terrestrial UEsand/or non-terrestrial UEs), other satellites in the one or more NTNdeployments, other types of BSs (e.g., stationary and/or ground-basedBSs), relay stations, one or more components and/or devices included ina core network of wireless network 100, and/or the like.

The wireless network 100 may be a heterogeneous network that includesbase stations 110 of different types, such as macro base stations, picobase stations, femto base stations, relay base stations, or the like.These different types of base stations 110 may have different transmitpower levels, different coverage areas, and/or different impacts oninterference in the wireless network 100. For example, macro basestations may have a high transmit power level (e.g., 5 to 40 watts)whereas pico base stations, femto base stations, and relay base stationsmay have lower transmit power levels (e.g., 0.1 to 2 watts).

A network controller 130 may couple to or communicate with a set of basestations 110 and may provide coordination and control for these basestations 110. The network controller 130 may communicate with the basestations 110 via a backhaul communication link. The base stations 110may communicate with one another directly or indirectly via a wirelessor wireline backhaul communication link.

The UEs 120 may be dispersed throughout the wireless network 100, andeach UE 120 may be stationary or mobile. A UE 120 may include, forexample, an access terminal, a terminal, a mobile station, and/or asubscriber unit. A UE 120 may be a cellular phone (e.g., a smart phone),a personal digital assistant (PDA), a wireless modem, a wirelesscommunication device, a handheld device, a laptop computer, a cordlessphone, a wireless local loop (WLL) station, a tablet, a camera, a gamingdevice, a netbook, a smartbook, an ultrabook, a medical device, abiometric device, a wearable device (e.g., a smart watch, smartclothing, smart glasses, a smart wristband, smart jewelry (e.g., a smartring or a smart bracelet)), an entertainment device (e.g., a musicdevice, a video device, and/or a satellite radio), a vehicular componentor sensor, a smart meter/sensor, industrial manufacturing equipment, aglobal positioning system device, and/or any other suitable device thatis configured to communicate via a wireless or wired medium.

Some UEs 120 may be considered machine-type communication (MTC) orevolved or enhanced machine-type communication (eMTC) UEs. An MTC UEand/or an eMTC UE may include, for example, a robot, a drone, a remotedevice, a sensor, a meter, a monitor, and/or a location tag, that maycommunicate with a base station, another device (e.g., a remote device),or some other entity. Some UEs 120 may be considered Internet-of-Things(IoT) devices, and/or may be implemented as NB-IoT (narrowband IoT)devices. Some UEs 120 may be considered a Customer Premises Equipment. AUE 120 may be included inside a housing that houses components of the UE120, such as processor components and/or memory components. In someexamples, the processor components and the memory components may becoupled together. For example, the processor components (e.g., one ormore processors) and the memory components (e.g., a memory) may beoperatively coupled, communicatively coupled, electronically coupled,and/or electrically coupled.

In general, any number of wireless networks 100 may be deployed in agiven geographic area. Each wireless network 100 may support aparticular RAT and may operate on one or more frequencies. A RAT may bereferred to as a radio technology, an air interface, or the like. Afrequency may be referred to as a carrier, a frequency channel, or thelike. Each frequency may support a single RAT in a given geographic areain order to avoid interference between wireless networks of differentRATs. In some cases, NR or 5G RAT networks may be deployed.

In some examples, two or more UEs 120 (e.g., shown as UE 120 a and UE120 e) may communicate directly using one or more sidelink channels(e.g., without using a base station 110 as an intermediary tocommunicate with one another). For example, the UEs 120 may communicateusing peer-to-peer (P2P) communications, device-to-device (D2D)communications, a vehicle-to-everything (V2X) protocol (e.g., which mayinclude a vehicle-to-vehicle (V2V) protocol, a vehicle-to-infrastructure(V2I) protocol, or a vehicle-to-pedestrian (V2P) protocol), and/or amesh network. In such examples, a UE 120 may perform schedulingoperations, resource selection operations, and/or other operationsdescribed elsewhere herein as being performed by the base station 110.

The electromagnetic spectrum is often subdivided, byfrequency/wavelength, into various classes, bands, channels, etc. In 5GNR, two initial operating bands have been identified as frequency rangedesignations FR1 (410 MHz-7.125 GHz) and FR2 (24.25 GHz-52.6 GHz). Itshould be understood that although a portion of FR1 is greater than 6GHz, FR1 is often referred to (interchangeably) as a “Sub-6 GHz” band invarious documents and articles. A similar nomenclature issue sometimesoccurs with regard to FR2, which is often referred to (interchangeably)as a “millimeter wave” band in documents and articles, despite beingdifferent from the extremely high frequency (EHF) band (30 GHz-300 GHz)which is identified by the International Telecommunications Union (ITU)as a “millimeter wave” band.

The frequencies between FR1 and FR2 are often referred to as mid-bandfrequencies. Recent 5G NR studies have identified an operating band forthese mid-band frequencies as frequency range designation FR3 (7.125GHz-24.25 GHz). Frequency bands falling within FR3 may inherit FR1characteristics and/or FR2 characteristics, and thus may effectivelyextend features of FR1 and/or FR2 into mid-band frequencies. Inaddition, higher frequency bands are currently being explored to extend5G NR operation beyond 52.6 GHz. For example, three higher operatingbands have been identified as frequency range designations FR4a or FR4-1(52.6 GHz-71 GHz), FR4 (52.6 GHz-114.25 GHz), and FR5 (114.25 GHz-300GHz). Each of these higher frequency bands falls within the EHF band.

With the above examples in mind, unless specifically stated otherwise,it should be understood that the term “sub-6 GHz” or the like, if usedherein, may broadly represent frequencies that may be less than 6 GHz,may be within FR1, or may include mid-band frequencies. Further, unlessspecifically stated otherwise, it should be understood that the term“millimeter wave” or the like, if used herein, may broadly representfrequencies that may include mid-band frequencies, may be within FR2,FR4, FR4-a or FR4-1, and/or FR5, or may be within the EHF band. It iscontemplated that the frequencies included in these operating bands(e.g., FR1, FR2, FR3, FR4, FR4-a, FR4-1, and/or FR5) may be modified,and techniques described herein are applicable to those modifiedfrequency ranges.

In some aspects, a first network node may refer to a receiver networknode that may include a communication manager 140 or a communicationmanager 150. As described in more detail elsewhere herein, thecommunication manager 140 or 150 may receive a signal; and transmit anAoD report that indicates at least one predicted AoD associated with adominant channel cluster, wherein the at least one predicted AoD isbased at least in part on the signal. For example, the first networknode may be the UE 120 a and, as shown by reference number 160, the UE120 a may receive a signal from the base station 110 a. As shown byreference number 170, the UE 120 a may transmit an AoD report to thebase station 110 a.

As described in more detail elsewhere herein, the first network node mayrefer to a transmitter network node, and the communication manager 140or 150 may transmit a signal; and receive an AoD report that indicatesat least one predicted AoD associated with a dominant channel cluster,wherein the at least one predicted AoD is based at least in part on thesignal. Additionally, or alternatively, the communication manager 140 or150 may perform one or more other operations described herein.

As indicated above, FIG. 1 is provided as an example. Other examples maydiffer from what is described with regard to FIG. 1 .

FIG. 2 is a diagram illustrating an example 200 of a base station 110 incommunication with a UE 120 in a wireless network 100, in accordancewith the present disclosure. The base station 110 may be equipped with aset of antennas 234 a through 234 t, such as T antennas (T≥1). The UE120 may be equipped with a set of antennas 252 a through 252 r, such asR antennas (R≥1).

At the base station 110, a transmit processor 220 may receive data, froma data source 212, intended for the UE 120 (or a set of UEs 120). Thetransmit processor 220 may select one or more modulation and codingschemes (MCSs) for the UE 120 based at least in part on one or morechannel quality indicators (CQIs) received from that UE 120. The basestation 110 may process (e.g., encode and modulate) the data for the UE120 based at least in part on the MCS(s) selected for the UE 120 and mayprovide data symbols for the UE 120. The transmit processor 220 mayprocess system information (e.g., for semi-static resource partitioninginformation (SRPI)) and control information (e.g., CQI requests, grants,and/or upper layer signaling) and provide overhead symbols and controlsymbols. The transmit processor 220 may generate reference symbols forreference signals (e.g., a cell-specific reference signal (CRS) or ademodulation reference signal (DMRS)) and synchronization signals (e.g.,a primary synchronization signal (PSS) or a secondary synchronizationsignal (SSS)). A transmit (TX) multiple-input multiple-output (MIMO)processor 230 may perform spatial processing (e.g., precoding) on thedata symbols, the control symbols, the overhead symbols, and/or thereference symbols, if applicable, and may provide a set of output symbolstreams (e.g., T output symbol streams) to a corresponding set of modems232 (e.g., T modems), shown as modems 232 a through 232 t. For example,each output symbol stream may be provided to a modulator component(shown as MOD) of a modem 232. Each modem 232 may use a respectivemodulator component to process a respective output symbol stream (e.g.,for OFDM) to obtain an output sample stream. Each modem 232 may furtheruse a respective modulator component to process (e.g., convert toanalog, amplify, filter, and/or upconvert) the output sample stream toobtain a downlink signal. The modems 232 a through 232 t may transmit aset of downlink signals (e.g., T downlink signals) via a correspondingset of antennas 234 (e.g., T antennas), shown as antennas 234 a through234 t.

In some aspects, the term “base station” (e.g., the base station 110),“network entity,” or “network node” may refer to an aggregated basestation, a disaggregated base station, an integrated access backhaul(IAB) node, a relay node, and/or one or more components thereof. Forexample, in some aspects, “base station,” “network entity,” or “networknode” may refer to a central (or centralized) unit (CU), a distributedunit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN IntelligentController (MC), or a Non-Real Time (Non-RT) RIC, or a combinationthereof. In some aspects, the term “base station,” “network entity,” or“network node” may refer to one device configured to perform one or morefunctions, such as those described herein in connection with the basestation 110. In some aspects, the term “base station,” “network entity,”or “network node” may refer to a plurality of devices configured toperform the one or more functions. For example, in some distributedsystems, each of a number of different devices (which may be located inthe same geographic location or in different geographic locations) maybe configured to perform at least a portion of a function, or toduplicate performance of at least a portion of the function, and theterm “base station,” “network entity,” or “network node” may refer toany one or more of those different devices. In some aspects, the term“base station,” “network entity,” or “network node” may refer to one ormore virtual base stations and/or one or more virtual base stationfunctions. For example, in some aspects, two or more base stationfunctions may be instantiated on a single device. In some aspects, theterm “base station,” “network entity,” or “network node” may refer toone of the base station functions and not another. In this way, a singledevice may include more than one base station.

At the UE 120, a set of antennas 252 (shown as antennas 252 a through252 r) may receive the downlink signals from the base station 110 and/orother base stations 110 and may provide a set of received signals (e.g.,R received signals) to a set of modems 254 (e.g., R modems), shown asmodems 254 a through 254 r. For example, each received signal may beprovided to a demodulator component (shown as DEMOD) of a modem 254.Each modem 254 may use a respective demodulator component to condition(e.g., filter, amplify, downconvert, and/or digitize) a received signalto obtain input samples. Each modem 254 may use a demodulator componentto further process the input samples (e.g., for OFDM) to obtain receivedsymbols. A MIMO detector 256 may obtain received symbols from the modems254, may perform MIMO detection on the received symbols if applicable,and may provide detected symbols. A receive processor 258 may process(e.g., demodulate and decode) the detected symbols, may provide decodeddata for the UE 120 to a data sink 260, and may provide decoded controlinformation and system information to a controller/processor 280. Theterm “controller/processor” may refer to one or more controllers, one ormore processors, or a combination thereof. A channel processor maydetermine an RSRP parameter, a received signal strength indicator (RSSI)parameter, a reference signal received quality (RSRQ) parameter, and/ora CQI parameter, among other examples. In some examples, one or morecomponents of the UE 120 may be included in a housing 284.

The network controller 130 may include a communication unit 294, acontroller/processor 290, and a memory 292. The network controller 130may include, for example, one or more devices in a core network. Thenetwork controller 130 may communicate with the base station 110 via thecommunication unit 294.

One or more antennas (e.g., antennas 234 a through 234 t and/or antennas252 a through 252 r) may include, or may be included within, one or moreantenna panels, one or more antenna groups, one or more sets of antennaelements, and/or one or more antenna arrays, among other examples. Anantenna panel, an antenna group, a set of antenna elements, and/or anantenna array may include one or more antenna elements (within a singlehousing or multiple housings), a set of coplanar antenna elements, a setof non-coplanar antenna elements, and/or one or more antenna elementscoupled to one or more transmission and/or reception components, such asone or more components of FIG. 2 .

Each of the antenna elements may include one or more sub-elements forradiating or receiving radio frequency signals. For example, a singleantenna element may include a first sub-element cross-polarized with asecond sub-element that can be used to independently transmitcross-polarized signals. The antenna elements may include patchantennas, dipole antennas, or other types of antennas arranged in alinear pattern, a two-dimensional pattern, or another pattern. A spacingbetween antenna elements may be such that signals with a desiredwavelength transmitted separately by the antenna elements may interactor interfere (e.g., to form a desired beam). For example, given anexpected range of wavelengths or frequencies, the spacing may provide aquarter wavelength, half wavelength, or other fraction of a wavelengthof spacing between neighboring antenna elements to allow for interactionor interference of signals transmitted by the separate antenna elementswithin that expected range.

Antenna elements and/or sub-elements may be used to generate beams.“Beam” may refer to a directional transmission such as a wireless signalthat is transmitted in a direction of a receiving device. A beam mayinclude a directional signal, a direction associated with a signal, aset of directional resources associated with a signal (e.g., angle ofarrival, horizontal direction, vertical direction), and/or a set ofparameters that indicate one or more aspects of a directional signal, adirection associated with a signal, and/or a set of directionalresources associated with a signal.

As indicated above, antenna elements and/or sub-elements may be used togenerate beams. For example, antenna elements may be individuallyselected or deselected for transmission of a signal (or signals) bycontrolling an amplitude of one or more corresponding amplifiers.Beamforming includes generation of a beam using multiple signals ondifferent antenna elements, where one or more, or all, of the multiplesignals are shifted in phase relative to each other. The formed beam maycarry physical or higher layer reference signals or information. As eachsignal of the multiple signals is radiated from a respective antennaelement, the radiated signals interact, interfere (constructive anddestructive interference), and amplify each other to form a resultingbeam. The shape (such as the amplitude, width, and/or presence of sidelobes) and the direction (such as an angle of the beam relative to asurface of an antenna array) can be dynamically controlled by modifyingthe phase shifts or phase offsets of the multiple signals relative toeach other.

Beamforming may be used for communications between a UE and a basestation, such as for millimeter wave communications and/or the like. Insuch a case, the base station may provide the UE with a configuration oftransmission configuration indicator (TCI) states that respectivelyindicate beams that may be used by the UE, such as for receiving aphysical downlink shared channel (PDSCH). The base station may indicatean activated TCI state to the UE, which the UE may use to select a beamfor receiving the PDSCH.

A beam indication may be, or include, a TCI state information element, abeam identifier (ID), spatial relation information, a TCI state ID, aclosed loop index, a panel ID, a TRP ID, and/or a sounding referencesignal (SRS) set ID, among other examples. A TCI state informationelement (referred to as a TCI state herein) may indicate informationassociated with a beam such as a downlink beam. For example, the TCIstate information element may indicate a TCI state identification (e.g.,a tci-StateID), a quasi-co-location (QCL) type (e.g., a qcl-Type1,qcl-Type2, qcl-TypeA, qcl-TypeB, qcl-TypeC, qcl-TypeD, and/or the like),a cell identification (e.g., a ServCellIndex), a bandwidth partidentification (bwp-Id), a reference signal identification such as aCSI-RS (e.g., an NZP-CSI-RS-ResourceId, an SSB-Index, and/or the like),and/or the like. Spatial relation information may similarly indicateinformation associated with an uplink beam.

The beam indication may be a joint or separate downlink (DL)/uplink (UL)beam indication in a unified TCI framework. In some cases, the networkmay support layer 1 (L1)-based beam indication using at leastUE-specific (unicast) downlink control information (DCI) to indicatejoint or separate DL/UL beam indications from active TCI states. In somecases, existing DCI formats 1_1 and/or 1_2 may be reused for beamindication. The network may include a support mechanism for a UE toacknowledge successful decoding of a beam indication. For example, theacknowledgment/negative acknowledgment (ACK/NACK) of the PDSCH scheduledby the DCI carrying the beam indication may be also used as an ACK forthe DCI.

Beam indications may be provided for carrier aggregation (CA) scenarios.In a unified TCI framework, information the network may support commonTCI state ID update and activation to provide common QCL and/or commonUL transmission spatial filter or filters across a set of configuredcomponent carriers (CCs). This type of beam indication may apply tointra-band CA, as well as to joint DL/UL and separate DL/UL beamindications. The common TCI state ID may imply that one reference signal(RS) determined according to the TCI state(s) indicated by a common TCIstate ID is used to provide QCL Type-D indication and to determine ULtransmission spatial filters across the set of configured CCs.

Some UEs and/or base stations may support full duplex operation in whichthe UEs and/or the base stations support full duplex operations. Forexample, a UE may support transmission via a first beam (e.g., using afirst antenna panel) and may simultaneously support reception via asecond beam (e.g., using a second antenna panel). Support forsimultaneous transmission and reception may be conditional on beamseparation, such as spatial separation (e.g., using different beams),frequency separation, and/or the like. Additionally, or alternatively,support for simultaneous transmission may be conditional on usingbeamforming (e.g., in frequency range 2 (FR2), in frequency range 4(FR4), for millimeter wave signals, and/or the like).

On the uplink, at the UE 120, a transmit processor 264 may receive andprocess data from a data source 262 and control information (e.g., forreports that include RSRP, RSSI, RSRQ, and/or CQI) from thecontroller/processor 280. The transmit processor 264 may generatereference symbols for one or more reference signals. The symbols fromthe transmit processor 264 may be precoded by a TX MIMO processor 266 ifapplicable, further processed by the modems 254 (e.g., for DFT-s-OFDM orCP-OFDM), and transmitted to the base station 110. In some examples, themodem 254 of the UE 120 may include a modulator and a demodulator. Insome examples, the UE 120 includes a transceiver. The transceiver mayinclude any combination of the antenna(s) 252, the modem(s) 254, theMIMO detector 256, the receive processor 258, the transmit processor264, and/or the TX MIMO processor 266. The transceiver may be used by aprocessor (e.g., the controller/processor 280) and the memory 282 toperform aspects of any of the methods described herein.

At the base station 110, the uplink signals from UE 120 and/or other UEsmay be received by the antennas 234, processed by the modem 232 (e.g., ademodulator component, shown as DEMOD, of the modem 232), detected by aMIMO detector 236 if applicable, and further processed by a receiveprocessor 238 to obtain decoded data and control information sent by theUE 120. The receive processor 238 may provide the decoded data to a datasink 239 and provide the decoded control information to thecontroller/processor 240. The base station 110 may include acommunication unit 244 and may communicate with the network controller130 via the communication unit 244. The base station 110 may include ascheduler 246 to schedule one or more UEs 120 for downlink and/or uplinkcommunications. In some examples, the modem 232 of the base station 110may include a modulator and a demodulator. In some examples, the basestation 110 includes a transceiver. The transceiver may include anycombination of the antenna(s) 234, the modem(s) 232, the MIMO detector236, the receive processor 238, the transmit processor 220, and/or theTX MIMO processor 230. The transceiver may be used by a processor (e.g.,the controller/processor 240) and the memory 242 to perform aspects ofany of the methods described herein.

The controller/processor 240 of the base station 110, thecontroller/processor 280 of the UE 120, and/or any other component(s) ofFIG. 2 may perform one or more techniques associated with indicating apredicted AoD, as described in more detail elsewhere herein. In someaspects, the network node described herein is the base station 110, isincluded in the base station 110, or includes one or more components ofthe base station 110 shown in FIG. 2 . In some aspects, the network nodedescribed herein is the UE 120, is included in the UE 120, or includesone or more components of the UE 120 shown in FIG. 2 . For example, thecontroller/processor 240 of the base station 110, thecontroller/processor 280 of the UE 120, and/or any other component(s) ofFIG. 2 may perform or direct operations of, for example, process 900 ofFIG. 9 , process 1000 of FIG. 10 , and/or other processes as describedherein. The memory 242 and the memory 282 may store data and programcodes for the base station 110 and the UE 120, respectively. In someexamples, the memory 242 and/or the memory 282 may include anon-transitory computer-readable medium storing one or more instructions(e.g., code and/or program code) for wireless communication. Forexample, the one or more instructions, when executed (e.g., directly, orafter compiling, converting, and/or interpreting) by one or moreprocessors of the base station 110 and/or the UE 120, may cause the oneor more processors, the UE 120, and/or the base station 110 to performor direct operations of, for example, process 900 of FIG. 9 , process1000 of FIG. 10 , and/or other processes as described herein. In someexamples, executing instructions may include running the instructions,converting the instructions, compiling the instructions, and/orinterpreting the instructions, among other examples.

In some aspects, a first network node includes means for receiving asignal; and/or means for transmitting an AoD report that indicates atleast one predicted AoD associated with a dominant channel cluster,wherein the at least one predicted AoD is based at least in part on thesignal. In some aspects, the first network node includes means fortransmitting a signal; and/or means for receiving an AoD report thatindicates at least one predicted AoD associated with a dominant channelcluster, wherein the at least one predicted AoD is based at least inpart on the signal. In some aspects, the means for the first networknode to perform operations described herein may include, for example,one or more of communication manager 150, transmit processor 220, TXMIMO processor 230, modem 232, antenna 234, MIMO detector 236, receiveprocessor 238, controller/processor 240, memory 242, or scheduler 246.In some aspects, the means for the first network node to performoperations described herein may include, for example, one or more ofcommunication manager 140, antenna 252, modem 254, MIMO detector 256,receive processor 258, transmit processor 264, TX MIMO processor 266,controller/processor 280, or memory 282.

While blocks in FIG. 2 are illustrated as distinct components, thefunctions described above with respect to the blocks may be implementedin a single hardware, software, or combination component or in variouscombinations of components. For example, the functions described withrespect to the transmit processor 264, the receive processor 258, and/orthe TX MIMO processor 266 may be performed by or under the control ofthe controller/processor 280.

As indicated above, FIG. 2 is provided as an example. Other examples maydiffer from what is described with regard to FIG. 2 .

FIG. 3 is a diagram illustrating an example 300 disaggregated basestation architecture, in accordance with the present disclosure.

Deployment of communication systems, such as 5G NR systems, may bearranged in multiple manners with various components or constituentparts. In a 5G NR system, or network, a “network node” may refer to anetwork entity, a mobility element of a network, a RAN node, a corenetwork node, a network element, or a network equipment, such as a basestation (BS, e.g., base station 110), or one or more units (or one ormore components) performing base station functionality, and may beimplemented in an aggregated or disaggregated architecture. For example,a BS (such as a Node B (NB), eNB, NR BS, 5G NB, access point (AP), aTRP, a cell, or the like) may be implemented as an aggregated basestation (also known as a standalone BS or a monolithic BS) or adisaggregated base station.

An aggregated base station may be configured to utilize a radio protocolstack that is physically or logically integrated within a single RANnode. A disaggregated base station may be configured to utilize aprotocol stack that is physically or logically distributed among two ormore units (such as one or more CUs, one or more DUs, or one or moreRUs). In some aspects, a CU may be implemented within a RAN node, andone or more DUs may be co-located with the CU, or alternatively, may begeographically or virtually distributed throughout one or multiple otherRAN nodes. The DUs may be implemented to communicate with one or moreRUs. Each of the CU, DU and RU also can be implemented as virtual units,i.e., a virtual centralized unit (VCU), a virtual distributed unit(VDU), or a virtual radio unit (VRU).

Base station-type operation or network design may consider aggregationcharacteristics of base station functionality. For example,disaggregated base stations may be utilized in an IAB network, an O-RAN(such as the network configuration sponsored by the O-RAN Alliance), ora virtualized radio access network (vRAN), also known as a cloud radioaccess network (C-RAN). Disaggregation may include distributingfunctionality across two or more units at various physical locations, aswell as distributing functionality for at least one unit virtually,which can enable flexibility in network design. The various units of thedisaggregated base station, or disaggregated RAN architecture, can beconfigured for wired or wireless communication with at least one otherunit.

The disaggregated base station architecture shown in FIG. 3 may includeone or more CUs 310 that can communicate directly with a core network320 via a backhaul link, or indirectly with the core network 320 throughone or more disaggregated base station units (such as a Near-RT RIC 325via an E2 link, or a Non-RT RIC 315 associated with a Service Managementand Orchestration (SMO) Framework 305, or both). A CU 310 maycommunicate with one or more DUs 330 via respective midhaul links, suchas an F1 interface. The DUs 330 may communicate with one or more RUs 340via respective fronthaul links. The RUs 340 may communicate withrespective UEs 120 via one or more RF access links. In someimplementations, the UE 120 may be simultaneously served by multiple RUs340.

Each of the units (e.g., the CUs 310, the DUs 330, the RUs 340), as wellas the Near-RT RICs 325, the Non-RT RICs 315, and the SMO Framework 305,may include one or more interfaces or be coupled to one or moreinterfaces configured to receive or transmit signals, data, orinformation (collectively, signals) via a wired or wireless transmissionmedium. Each of the units, or an associated processor or controllerproviding instructions to the communication interfaces of the units, canbe configured to communicate with one or more of the other units via thetransmission medium. For example, the units can include a wiredinterface configured to receive or transmit signals over a wiredtransmission medium to one or more of the other units. Additionally, theunits can include a wireless interface, which may include a receiver, atransmitter or transceiver (such as an RF transceiver), configured toreceive or transmit signals, or both, over a wireless transmissionmedium to one or more of the other units.

In some aspects, the CU 310 may host one or more higher layer controlfunctions. Such control functions can include radio resource control(RRC), packet data convergence protocol (PDCP), service data adaptationprotocol (SDAP), or the like. Each control function can be implementedwith an interface configured to communicate signals with other controlfunctions hosted by the CU 310. The CU 310 may be configured to handleuser plane functionality (e.g., Central Unit—User Plane (CU-UP)),control plane functionality (e.g., Central Unit—Control Plane (CU-CP)),or a combination thereof. In some implementations, the CU 310 can belogically split into one or more CU-UP units and one or more CU-CPunits. The CU-UP unit can communicate bidirectionally with the CU-CPunit via an interface, such as the E1 interface when implemented in anO-RAN configuration. The CU 310 can be implemented to communicate withthe DU 330, as necessary, for network control and signaling.

The DU 330 may correspond to a logical unit that includes one or morebase station functions to control the operation of one or more RUs 340.In some aspects, the DU 330 may host one or more of a radio link control(RLC) layer, a medium access control (MAC) layer, and one or more highphysical (PHY) layers (such as modules for forward error correction(FEC) encoding and decoding, scrambling, modulation and demodulation, orthe like) depending, at least in part, on a functional split, such asthose defined by the 3GPP. In some aspects, the DU 330 may further hostone or more low-PHY layers. Each layer (or module) can be implementedwith an interface configured to communicate signals with other layers(and modules) hosted by the DU 330, or with the control functions hostedby the CU 310.

Lower-layer functionality can be implemented by one or more RUs 340. Insome deployments, an RU 340, controlled by a DU 330, may correspond to alogical node that hosts RF processing functions, or low-PHY layerfunctions (such as performing fast Fourier transform (FFT), inverse FFT(iFFT), digital beamforming, physical random access channel (PRACH)extraction and filtering, or the like), or both, based at least in parton the functional split, such as a lower layer functional split. In suchan architecture, the RU(s) 340 can be implemented to handle over the air(OTA) communication with one or more UEs 120. In some implementations,real-time and non-real-time aspects of control and user planecommunication with the RU(s) 340 can be controlled by the correspondingDU 330. In some scenarios, this configuration can enable the DU(s) 330and the CU 310 to be implemented in a cloud-based RAN architecture, suchas a vRAN architecture.

The SMO Framework 305 may be configured to support RAN deployment andprovisioning of non-virtualized and virtualized network elements. Fornon-virtualized network elements, the SMO Framework 305 may beconfigured to support the deployment of dedicated physical resources forRAN coverage requirements which may be managed via an operations andmaintenance interface (such as an O1 interface). For virtualized networkelements, the SMO Framework 305 may be configured to interact with acloud computing platform (such as an open cloud (O-Cloud) 390) toperform network element life cycle management (such as to instantiatevirtualized network elements) via a cloud computing platform interface(such as an O2 interface). Such virtualized network elements caninclude, but are not limited to, CUs 310, DUs 330, RUs 340 and Near-RTRICs 325. In some implementations, the SMO Framework 305 can communicatewith a hardware aspect of a 4G RAN, such as an open eNB (O-eNB) 311, viaan O1 interface. Additionally, in some implementations, the SMOFramework 305 can communicate directly with one or more RUs 340 via anO1 interface. The SMO Framework 305 also may include a Non-RT RIC 315configured to support functionality of the SMO Framework 305.

The Non-RT RIC 315 may be configured to include a logical function thatenables non-real-time control and optimization of RAN elements andresources, Artificial Intelligence/Machine Learning (AI/ML) workflowsincluding model training and updates, or policy-based guidance ofapplications/features in the Near-RT RIC 325. The Non-RT RIC 315 may becoupled to or communicate with (such as via an A1 interface) the Near-RTRIC 325. The Near-RT RIC 325 may be configured to include a logicalfunction that enables near-real-time control and optimization of RANelements and resources via data collection and actions over an interface(such as via an E2 interface) connecting one or more CUs 310, one ormore DUs 330, or both, as well as an O-eNB, with the Near-RT RIC 325.

In some implementations, to generate AI/ML models to be deployed in theNear-RT RIC 325, the Non-RT RIC 315 may receive parameters or externalenrichment information from external servers. Such information may beutilized by the Near-RT RIC 325 and may be received at the SMO Framework305 or the Non-RT RIC 315 from non-network data sources or from networkfunctions. In some examples, the Non-RT RIC 315 or the Near-RT RIC 325may be configured to tune RAN behavior or performance. For example, theNon-RT RIC 315 may monitor long-term trends and patterns for performanceand employ AI/ML models to perform corrective actions through the SMOFramework 305 (such as reconfiguration via 01) or via creation of RANmanagement policies (such as A1 policies).

As indicated above, FIG. 3 is provided as an example. Other examples maydiffer from what is described with regard to FIG. 3 .

FIGS. 4A and 4B are diagrams illustrating an example 400 of analogbeamforming for millimeter wave communications, in accordance with thepresent disclosure. As shown, a receiver network node 402 and atransmitter network node 404 may communicate with one another.

As shown in FIG. 4A, the receiver network node 402 may include abeamforming architecture 406. In some aspects, the architecture 406 mayimplement aspects of wireless network 100. For example, the architecture406 may show receive chains (e.g., RF chains) for reception ofcommunications by the receiver network node 402. The architecture 406may be particularly useful for communication in a millimeter wave range,such as FR2 and/or the like.

Broadly, FIG. 4A is a diagram illustrating example hardware componentsof a wireless communication device in accordance with certain aspects ofthe disclosure. The illustrated components may include those that may beused for antenna element selection and/or for beamforming for receptionof wireless signals. There are numerous architectures for antennaelement selection and implementing phase shifting, only two examples ofwhich are illustrated here. Transmission lines or other waveguides,wires, traces, and/or the like are shown connecting the variouscomponents to illustrate how signals to be transmitted may travelbetween components.

The architecture 406 includes a hybrid beamforming architecture. Thearchitecture 406 includes an antenna array 408. The antenna array 408includes N antenna elements 410. An antenna element 410 can include oneor more sub-elements 412 for radiating or receiving RF signals. Forexample, a single antenna element 410 can include a first sub-element412 cross-polarized with a second sub-element 412 that can be used toindependently transmit or receive cross-polarized signals. The antennaelements 410 can include patch antennas, dipole antennas, or other typesof antennas arranged in a linear pattern, a two-dimensional pattern, oranother pattern. A spacing between antenna elements 410 can be such thatsignals with a desired wavelength transmitted separately by the antennaelements 410 can interact or interfere (e.g., to form a desired beam).For example, given an expected range of wavelengths or frequencies, thespacing may provide a quarter wavelength, half wavelength, or otherfraction of a wavelength of spacing between neighboring antenna elements410 to allow for interaction or interference of signals transmitted bythe separate antenna elements 410 within that expected range.

A signal {tilde over (y)}_(n)(t) received at an antenna element n at atime t can propagate to an analog beamformer 414 (referred tointerchangeably as an “AFB”). The analog beamformer 414 can include aplurality of phase shifters 416 and one or more amplifiers 418 (e.g.,one amplifier 418 per RF chain, multiple amplifiers 418 per RF chain, orone amplifier 418 for multiple RF chains). The architecture 406 includesa plurality of RF chains 420 (e.g., N_(RF) RF chains). N_(RF) may besmaller than N (e.g., the number of RF chains 420 may be smaller thanthe number of antenna elements of the architecture 406). In someexamples, N_(RF) may be 2 or 4. An architecture including a plurality ofRF chains 420 and analog phase shifters 416 and amplifiers 418 can bereferred to as a hybrid beamforming architecture. An architectureincluding a single RF chain (e.g., N_(RF)=1) may be referred to as ananalog beamforming architecture.

Each RF chain 420 of architecture 406 can be associated with arespective analog-to-digital converter (ADC) 422. The ADCs 422 of the RFchains 420 can perform analog-to-digital conversion of the signalsreceived from the analog beamformer 414. The ADCs 422 provide digitalsignals y1[n] through y_(N) _(RF) [n] to a digital beamformer 424(referred to interchangeably as a “DBF”). The digital beamformer 424 canbe implemented at the baseband or can interface with a basebandprocessor. The digital beamformer 424 may perform digital-domain signalprocessing, such as digital baseband processing, controlling operationof components 408/410/412/414/416/418/420/422, spatial configuration ofthe communication of the receiver network node 402, and so on. In someaspects, the digital beamformer 424 can be a component of acommunication manager 426. The communication manager 426 can be, besimilar to, include, or be included in, the communication manager 140depicted in FIGS. 1 and 2 , the communication manager 150 depicted inFIGS. 1 and 2 , and/or the communication manager 1108 depicted in FIG.11 .

As shown in FIG. 4B, the transmitter network node 404 includes anantenna array 428. The antenna array 428 can include M antenna elements430. Each antenna element 430 may include one or more sub-elements 432.The transmitter network node 404 can include an analog beamformer 434and a digital beamformer 436 connected to the analog beamformer 434 viaone or more digital-to-analog converters (DACs) 438.

To facilitate mmW communications, the receiver network node 402 and thetransmitter network node 404 can perform a beam management procedure inwhich the receiver network node 402 and the transmitter network node 404identify beam pairs to be used for communication. In some cases, forexample, the receiver network node 402 and the transmitter network node404 can perform beam management.

For example, the receiver network node 402 and the transmitter networknode 404 can perform a first beam management procedure. The first beammanagement procedure can be referred to as a “P1” procedure, a beamselection procedure, an initial beam acquisition procedure, a beamsweeping procedure, a cell search procedure, and/or a beam searchprocedure. In the first beam management procedure, channel stateinformation (CSI)-reference signals (CSI-RSs) can be configured to betransmitted from the transmitter network node 404 to the receivernetwork node 402. The first beam management procedure can include thetransmitter network node 404 performing beam sweeping over multiple Txbeams (shown as “B₁,” “B₂,” . . . “B_(k),” . . . “B_(m−1),” and“B_(m)”). The transmitter network node 404 can transmit a CSI-RS usingeach transmit beam for beam management. To enable the receiver networknode 402 to perform Rx beam sweeping, the transmitter network node 404can use a transmit beam to transmit (e.g., with repetitions) each CSI-RSat multiple times within the same RS resource set so that the receivernetwork node 402 can sweep through receive beams in multipletransmission instances. As a result, the first beam management procedurecan enable the receiver network node 402 to measure a CSI-RS ondifferent transmit beams using different receive beams to supportselection of a pair of beams that includes a transmission beam and areception beam. The receiver network node 402 can report themeasurements to the transmitter network node 404 to enable thetransmitter network node 404 to select one or more beam pair(s) forcommunication between the transmitter network node 404 and the receivernetwork node 402. In some cases, the first beam management process canalso use synchronization signal blocks (SSBs) for beam management in asimilar manner as described above.

In some cases, the receiver network node 402 and the transmitter networknode 404 can perform a second beam management procedure. The second beammanagement procedure can be referred to as a “P2” beam managementprocedure, a beam refinement procedure, a base station beam refinementprocedure, a TRP beam refinement procedure, and/or a transmit beamrefinement procedure. In the second beam management procedure, CSI-RSscan be configured to be transmitted from the transmitter network node404 to the receiver network node 402. The second beam managementprocedure can include the transmitter network node 404 performing beamsweeping over one or more transmit beams. The one or more transmit beamscan be a subset of all transmit beams associated with the transmitternetwork node 404 (e.g., determined based at least in part onmeasurements reported by the receiver network node 402 in connectionwith the first beam management procedure). The transmitter network node404 can transmit a CSI-RS using each transmit beam of the one or moretransmit beams for beam management. The receiver network node 402 canmeasure each CSI-RS using a single (e.g., a same) receive beam (e.g.,determined based at least in part on measurements performed inconnection with the first beam management procedure). The second beammanagement procedure can enable the transmitter network node 404 toselect a transmit beam based at least in part on measurements of theCSI-RSs (e.g., measured by the receiver network node 402 using thesingle receive beam) reported by the receiver network node 402.

In some cases, the receiver network node 402 and the transmitter networknode 404 can perform a third beam management procedure. The third beammanagement procedure can be referred to as a “P3” beam managementprocedure, a beam refinement procedure, a UE beam refinement procedure,and/or a receive beam refinement procedure. In a third beam managementprocedure, one or more CSI-RSs can be configured to be transmitted fromthe transmitter network node 404 to the receiver network node 402. Thethird beam management procedure can include the transmitter network node404 transmitting the one or more CSI-RSs using a single transmit beam(e.g., determined based at least in part on measurements reported by thereceiver network node 402 in connection with the first beam managementprocedure and/or the second beam management procedure). To enable thereceiver network node 402 to perform receive beam sweeping, thetransmitter network node 404 can use a transmit beam to transmit (e.g.,with repetitions) CSI-RS at multiple times within the same RS resourceset so that receiver network node 402 can sweep through one or morereceive beams in multiple transmission instances. The one or morereceive beams can be a subset of all receive beams associated with thereceiver network node 402 (e.g., determined based at least in part onmeasurements performed in connection with the first beam managementprocedure and/or the second beam management procedure). The third beammanagement procedure can enable the transmitter network node 404 and/orthe receiver network node 402 to select a best receive beam based atleast in part on reported measurements received from the receivernetwork node 402 (e.g., of the CSI-RS of the transmit beam using the oneor more receive beams).

In performing the beam management procedures described above, thereceive and transmit beams are selected from respective beamformingcodebooks. For example, to determine receive beams to use, the receiverdetermines a hybrid beamforming signal estimate, y, based on a hybridbeamforming input-output relationship per tone that is expressed as y interms of a variable, x, and a variable, n:y=AHBPx+n,where, A is an Rx analog beamforming matrix, H is a raw channel matrix,B is a Tx analog beamforming matrix, and P is a Tx digital precodingmatrix. The Rx analog beamforming matrix A is a linear transform and thesize of the matrix A is N_(RP)×N_(Rx), where N_(RP) is the number of RFchains in the receiver, and N_(Rx) is the number of receive antennas.The size of the raw channel matrix H is N_(Rx)×N_(Tx), where N_(Rx) isthe number of receive antennas and N_(Tx) is the number of transmitantennas. The raw channel matrix H is a function of core parametersincluding, for example, per-cluster AoA and AoD delays, and gains. Thesize of the Tx analog beamforming matrix B is N_(Tx)×N_(TP), whereN_(TP) is the number of RF chains at the transmitter and N_(Tx) is thenumber of transmit antennas. The size of the Tx digital precoding matrixis N_(TP)×N_(SS), where N_(SS) is the number of spatial streams.

In the beamforming procedures described above, A and B are chosen fromanalog beamforming codebooks, which can include sets of phase shifts toapply to antenna elements and/or amplitude coefficients. A is chosen bythe receiver network node 402 and B and P are chosen by the transmitternetwork node 404. The transmitter network node 404 determines the beamsto use (e.g., by choosing B and P), from a transmitter network nodebeamforming codebook, based on RSRP measurements reported by thereceiver network node 402. However, the beamforming codebooks may not becustomized to the specific channel H, as they are pre-defined codebooksconfigured to facilitate generation of pre-defined beams. In some cases,a pair of corresponding angles (AoA and AoD) of the channel cluster 440might facilitate a better communication channel than any of the beamsindicated in the beamforming codebooks (e.g., beams B1-Bm).

Some aspects of the techniques and apparatuses described herein mayfacilitate using non-codebook beams for beamforming a communicationbetween a transmitter network node and a receiver network node. Forexample, in some aspects, a receiver network node may use observationsabout analog beamformed channels to determine a channel estimate of theunderlying channel (e.g., the raw channel represented by H). Theestimate of the underlying channel may be used to predict an AoD, whichmay be indicated to the transmitter network node 404 to facilitatebeamforming.

For example, as shown in FIGS. 4B and 4C, a channel cluster 440 isillustrated as a combination of a Tx path (represented by an AoD 442 anda gain along the AoD 442) and an Rx path (represented by an AoA 444 anda gain along the AoA 444). As shown in FIG. 4C, for example, the AoD 442and AoA 444 may be represented in the context of a respective sphericalcoordinate system 446 or 448. In some examples, the coordinate system446 and the coordinate system 448 may be the same system. In some otherexamples, the coordinate system 446 may be different than the coordinatesystem 448 (e.g., different in orientation and/or scale). As shown, theAoD 442 may include a path (e.g., a direction) determined by acombination of an AaoD 450 and an AzoD 452. The AaoD 450 may be an angleof azimuth defined with respect to an azimuthal axis 454, and the AzoD452 may be an angle of zenith defined with respect to a zenith axis 456.Similarly, the AoA 444 may include a path (e.g., a direction) determinedby a combination of an AaoA 458 and an AzoA 460. The AaoA 458 may be anangle of azimuth defined with respect to an azimuthal axis 462, and theAzoA 460 may be an angle of zenith defined with respect to a zenith axis464.

The channel estimate may be obtained using a sparse recovery procedurethat facilitates a lower dimension observation of higher dimensionvariables. For example, in example 400, the receiver network node 402includes four dual-polarization antenna elements 410 and the transmitternetwork node 404 includes 32 dual-polarization antenna elements 430.Thus, the dimensionality of the channel H is 8×64. Since each 2×2 beampair provides a beamformed observation of H, the dimensionality of theRx analog beamforming matrix A is 2×8, and the dimensionality of the Txanalog beamforming matrix B is 64×2. Therefore, the dimensionality ofthe effective channel, AHB=(2×8)×(8×64)×(64×2)=2×2, which is a muchsmaller dimensionality than 8×64, the dimensionality of the channel H inthe frequency domain.

However, the channel may be represented in the time domain (e.g., thedelay tap domain). For example, as shown in FIG. 4B, the delay tapdomain refers to a time domain defined according to a series of delaytaps 466 (e.g., measurement points), separated by a delay, i, along adelay line 468 associated with the channel. In the delay tap domain, thed^(th) delay tap of the channel is composed of multiple channel clusters(e.g., up to L clusters). Each channel cluster (e.g., the channelcluster 440) is associated with an AoA/AoD pair (e.g., the AoA 444 andAoD 442) the corresponding gains along those angles. As described above,the AoA 444 and the AoD 442 each include angles of azimuth and angles ofelevation. It has been observed that, in the delay tap domain, thechannel is sparse because the channel includes only a small number(e.g., two or three) dominant channel clusters (illustrated as channelcluster 440 and channel cluster 470). Accordingly, the receiver networknode 402 may recover the underlying channel using only a few beamformedmeasurements. The estimated channel may be used to facilitate beamselection without an unnecessary increase in overhead or powerconsumption since the underlying channel is estimated using a sparserecovery operation.

For example, as shown in FIG. 4B, in some aspects, the receiver networknode 402 may receive a signal 472 from the transmitter network node 404.The receiver network node 402 may determine at least one predicted AoD474 associated with a dominant channel cluster (e.g., channel cluster440) based at least in part on the signal 472. In some aspects, thereceiver network node 402 may determine the at least one predicted AoD474 based at least in part on a sparse recovery operation. The sparserecovery operation may include, for example, a machine learningoperation or a compressed sensing operation. As shown, the receivernetwork node 402 may transmit an AoD report 476 to the transmitternetwork node 404. The AoD report may indicate the at least one predictedAoD 474 to facilitate non-codebook analog beamforming.

In some aspects, the at least one predicted AoD 474 may enable thetransmitter network node 404 to generate a custom transmission beam 478and/or the receiver network node 402 to generate a custom reception beam480 in a direction based on a strongest channel cluster (e.g., channelcluster 440). Using one or more of these custom beams 478 or 480 mayimprove spectral efficiency and/or angular resolution (e.g., the abilityof the network node 402 to discern AoAs) as compared to using codebookbeams (e.g., A1-An or B1-Bm). Improved angular resolution and spectralefficiency may facilitate more efficient communications with higherthroughput, thereby resulting in a positive impact on networkperformance.

As indicated above, FIGS. 4A and 4B are provided as examples. Otherexamples may differ from what is described with regard to FIGS. 4A and4B.

FIG. 5 is a diagram illustrating an example 500 associated withpredicting AoDs, in accordance with the present disclosure. As shown inFIG. 5 , a receiver network node 505 and a transmitter network node 510may communicate with one another. The transmitter network node 510 maybe, or be similar to, the transmitter network node 404 shown in FIG. 4 ,and the receiver network node 505 may be, or be similar to, the receivernetwork node 402 shown in FIG. 4 . In some aspects, the receiver networknode 505 may be referred to as a “first network node” and thetransmitter network node 510 may be referred to as a “second networknode.” In some other aspects, the transmitter network node 510 may bereferred to as a “first network node” and the receiver network node 505may be referred to as a “second network node.”

As shown by reference number 515, the transmitter network node 510 maytransmit, and the receiver network node 505 may receive, an AoD reportconfiguration. The AoD report configuration may indicate a format of anAoD report. For example, the AoD report configuration may indicate atype of signal to be used to transmit the AoD report, data fields to beincluded in the AoD report, and/or expected data values to be indicatedby the data fields, among other examples.

As shown by reference number 520, the transmitter network node 510 maytransmit, and the receiver network node 505 may receive, a signal. Insome aspects, the signal may include a reference signal. The signal maybe associated with a transmission beam of a plurality of transmissionbeams.

As shown by reference number 525, the receiver network node 505 mayobtain a beam measurement associated with the transmission beam. Thereceiver network node 505 may obtain the beam measurement based at leastin part on at least one reception beam used to receive the signal. Thebeam measurement may be associated with at least one beam pair, of a setof beam pairs. In some aspects, the receiver network node 505 may obtainmeasurements for a plurality of beam pairs. Each beam pair of the set ofbeam pairs may include a transmission beam of the plurality oftransmission beams and a reception beam of the at least one receptionbeam. The at least one beam pair may correspond to a subset of RSRPmeasurements having largest RSRP values of a set of RSRP valuesassociated with the set of beam pairs.

As shown by reference number 530, the receiver network node 505 maydetermine at least one predicted AoD. The at least one predicted AoD mayinclude a predicted azimuth AoD and/or a predicted elevation AoD. The atleast one predicted AoD may be associated with a dominant channelcluster. The receiver network node 505 may determine the at least onepredicted AoD based at least in part on a sparse recovery operation. Thesparse recovery operation may include a machine learning operation or acompressed sensing operation. The receiver network node 505 maydetermine the at least one predicted AoD based at least in part onperforming the sparse recovery operation using the beam measurement asan input to the sparse recovery operation.

As shown by reference number 535, the receiver network node 505 maytransmit, and the transmitter network node 510 may receive, an AoDreport. The AoD report may indicate the at least one predicted AoD. Insome aspects, the receiver network node 505 may transmit a dedicated AoDreport. In other aspects, the AoD report may include a per-path AoAreport that indicates the at least one predicted AoD. The AoD report mayindicate at least one estimated channel gain associated with the atleast one predicted AoD. The AoD report may indicate the at least onepredicted AoD based at least in part on indicating at least onequantized predicted AoD. The AoD report may indicate the at least oneestimated channel gain based at least in part on indicating at least onequantized estimated channel gain.

In some aspects, the AoD report may indicate at least one confidencelevel associated with the at least one predicted AoD. For example, theat least one confidence level may indicate one of three values. Thethree values may include a first value that indicates a low confidence,a second value that indicates a medium confidence, and a third valuethat indicates a high confidence.

As shown by reference number 540, the transmitter network node 510 maytransmit, and the receiver network node 505 may receive, a beamselection indication. The beam selection indication may include a customindication or a codebook indication. A custom indication may indicatethat at least one additional signal to be transmitted is associated witha custom transmission beam. The custom transmission beam may be atransmission beam that is not associated with a beamforming codebook.Similarly, the receiver network node 505 may use a custom reception beambased at least in part on at least one predicted AoA associated with theat least one predicted AoD.

A codebook indication may indicate that the at least one additionalsignal is associated with a codebook beam. For example, the codebookindication may indicate that the at least one additional signal isassociated with a codebook beam based at least in part on the predictedAoD being within a threshold angle of the codebook beam.

As shown by reference number 545, the transmitter network node 510 maytransmit, and the receiver network node 505 may receive, at least oneadditional signal associated with the predicted AoD. The at least oneadditional signal may include, for example, a data transmission signal.In some aspects, the at least one additional signal may be associatedwith the custom transmission beam or the codebook beam. The receivernetwork node 505 may receive the at least one additional signal using acustom reception beam based at least in part on receiving the customindication. The receiver network node 505 may receive the at least oneadditional signal using a codebook reception beam based at least in parton receiving the codebook indication. The receiver network node 505 mayreceive the at least one additional signal corresponding to a customtransmission beam based at least in part on the at least one confidencelevel indicating the third value (e.g., a high confidence associatedwith the at least one predicted AoD).

As indicated above, FIG. 5 is provided as an example. Other examples maydiffer from what is described with regard to FIG. 5 .

As discussed above, in connection with FIG. 5 , the receiver networknode 505 may be configured to determine at least one predicted AoD basedat least in part on a signal received from the transmitter network node510. To determine the at least one predicted AoD, the receiver networknode 505 may be configured to use a sparse recovery operation todetermine an estimate of the communication channel.

FIGS. 6A and 6B are diagrams illustrating an example 600 associated withusing a sparse recovery operation to predict an AoD, in accordance withthe present disclosure. As shown, a receiver network node 602 and atransmitter network node 604 may communicate with one another. In someaspects, the receiver network node 602 may be referred to as a “firstnetwork node” and the transmitter network node 604 may be referred to asa “second network node.” In some other aspects, the transmitter networknode 604 may be referred to as a “first network node” and the receivernetwork node 602 may be referred to as a “second network node.” Thereceiver network node 602 may be, or be similar to, the receiver networknode 505 depicted in FIG. 5 and/or the receiver network node 402depicted in FIGS. 4A and 4B. The transmitter network node 604 may be, orbe similar to, the transmitter network node 510 depicted in FIG. 5and/or the transmitter network node 404 depicted in FIGS. 4A and 4B.

As shown, for example, the receiver network node 602 may include anantenna array 606. The antenna array 606 may include N antenna elements608. The antenna array 606 may be connected to an analog beamformer(“ABF”) 610, which may be connected to a DBF 612 via one or more ADCs614. The transmitter network node 604 may include an antenna array 616.The antenna array 616 may include M antenna elements 618. The antennaarray 616 may be connected to an analog beamformer (“ABF”) 620, whichmay be connected to a digital precoder (“DPC”) 622 via one or more DACs624.

As shown, the receiver network node 602 may be configured to determine achannel estimate, H_(d), for each d^(th) delay tap 626 along a delayline 628 corresponding to a delay spread associated with a wirelesscommunication channel H. In some aspects, the receiver network node 602may include (e.g., stored in memory) a beamforming codebook thatincludes 4 beams and an oversampled codebook (oversampled in the spatialdomain) that includes 16 beams. The transmitter network node 404 mayinclude a beamforming codebook that includes 32 beams and an oversampledcodebook that includes 128 beams.

In some aspects, instead of beam sweeping over the entire oversampledbeamforming codebook of the receiver network node 602 to estimate thechannel, the receiver network node 602 may use only codebook beams(e.g., beams B1, B2, Bi, Bj, and Bm) in connection with a sparserecovery operation to estimate the channel. Based on the estimatedchannel, as explained above in connection with FIG. 5 , the receivernetwork node 602 may predict at least one AoD, which may be used by thereceiver network node 602 to determine a custom, non-codebook beam, or acodebook beam, and by the transmitter network node 604 to determine acustom or codebook beam. Because the receiver network node 602 does nothave to sweep over the over-sampled codebook, some aspects mayfacilitate overhead reduction and power savings at the receiver networknode 602, while improving throughput.

To estimate the channel, the receiver network node 602 may receive asignal 630 from the transmitter network node 604. In some aspects, thesignal 630 may represent a plurality of signals. The receiver networknode 602 may use the signal 630 to perform the sparse recovery operationbased at least in part on a geometric channel model forfrequency-selective mmW channel consisting of L clusters. A geometricchannel model representation is a model of a channel in the delay tapdomain. Thus, for example, determining an FFT of the channel in the tapdomain results in a model of the channel in the frequency domain. If thechannel has a total of N_(d) taps, the d^(th) delay tap of the channel(for d=1, 2, . . . , N_(d)) can be expressed as

${H_{d} = {\sum_{l = 1}^{L}{\alpha_{l}{s\left( {{dT_{s}} - \tau_{l}} \right)}{p_{R}\left( {\theta_{R_{l}},\phi_{R_{l}}} \right)}{p_{T}^{*}\left( {\theta_{T_{l}},\phi_{T_{l}}} \right)}}}},$where α_(l) is the complex gain of the l^(th) channel cluster, s(τ) is aband-limited pulse shaping filter response evaluated at i, p_(R)(θ_(R)_(l) , ϕ_(R) _(l) ) is a receiver antenna element response vector, andp_(T)(θ_(T) _(l) , ϕ_(T) _(l) ) is a transmitter antenna elementresponse vector.

The above equation can be re-written in the matrix form as follows:H _(d) ={tilde over (P)} _(R)Δ_(d) {tilde over (P)} _(T)*,where Δ_(d) is an [L×L] diagonal matrix with non-zero complex entries,{tilde over (P)}_(R) is an [N_(UEant)×L] matrix including the receivernetwork node 602 antenna element 608 responses for L clusters, and{tilde over (P)}_(T) is an [N_(NBant)×L] matrix including thetransmitter network node 604 element responses for L clusters.

As shown in FIG. 6A, the receiver network node 602 may generate aquantized channel representation by using a first two-dimensional grid632 to quantize the angular space at the transmitter network node 604and a second two-dimensional grid 634 to quantize the angular space atthe receiver network node 602. The grids 632 and 634 may be used todivide up the angular space. The dimensions of the grids 632 and 634 maybe customizable. In the illustrated example, each grid is divided using16 dimensions. In some aspects, the first network grid 632 may, forexample, include 32 elevation dimensions and 64 azimuth dimensions. Inthe illustrated example, each grid 632 and 634 may be configured todivide the angular space from −180 degrees to 180 degrees in the azimuthdirection 636 and from 0 degrees to 180 degrees in the elevationdirection 638.

In some aspects, the illustrated grids 632 and 634 may be used todetermine underlying H channels from multiple 2×2 AHB measurements. Forexample, a 128×128 grid and a 128×128 grid may correspond to aquantization based on the AoAs and AoDs, respectively. Then, the d^(th)delay tap of the extended virtual channel model can be written asH _(d) ≈P _(R)Δ_(d) ^(v) P _(T)*,where P_(R) is the receiver element response matrix evaluated at eachgrid point, Δ_(d) ^(v) is a large sparse matrix in which the non-zeroelements of the matrix represent the channel gains along certain angles,where the angles correspond to certain rows and columns of the matrix.Thus, for example, if a certain row and column of the Δ_(d) ^(v) matrixis non-zero, there is a channel cluster along the associated angles andthe gain of the channel cluster is denoted by the non-zero element. Forexample, the gain of the cluster 640 is the gain along an AoD 642 and anAoA 644. P_(T)* is the transmitter element response matrix evaluated ateach grid point. Accordingly, the representation of equation 4 indicatesthat, for a given channel tap, the dimension of H_(d) is 8×64, thusquantizing the channel in the angular domain.

As shown in FIG. 6C, for example, the AoD 642 and AoA 644 may berepresented in the context of a respective spherical coordinate system646 or 648. In some examples, the coordinate system 646 and thecoordinate system 648 may be the same system. In some other examples,the coordinate system 646 may be different than the coordinate system648 (e.g., different in orientation and/or scale). As shown, the AoD 642may include a path (e.g., a direction) determined by a combination of anAaoD 650 and an AzoD 652. The AaoD 650 may be an angle of azimuthdefined with respect to an azimuthal axis 654, and the AzoD 652 may bean angle of zenith defined with respect to a zenith axis 656. Similarly,the AoA 644 may include a path (e.g., a direction) determined by acombination of an AaoA 658 and an AzoA 660. The AaoA 658 may be an angleof azimuth defined with respect to an azimuthal axis 662, and the AzoA660 may be an angle of zenith defined with respect to a zenith axis 664.

To quantize the channel in the angular domain, angles associated with anumber of points along the AoA 644 may be mapped to closest grid points.For example, as shown in FIG. 6A, a point 666 associated with the AoA644 may be mapped to a closest grid point 668 of the four grid pointsadjacent to the point 666. Repeating this mapping for a plurality ofpoints along the AoA 644 results in a large sparse matrix (e.g., many ofthe values of the matrix will be zero), represented by P_(R) and P_(T)*.The gain will be shown in the Δ_(d) ^(v) matrix. A similar mappingprocedure may be performed associated with the AoD 644. Thedimensionalities of the terms are as follows:P _(R):[8×128²], Δ_(d) ^(v)[128²×128²], and P _(T)*[128²×64].

The channel may be rewritten in vectorized format, using the Kroneckerproduct:vec(H _(d))≈vec(P _(R)Δ_(d) ^(v) P _(T)*)=[(P _(T)*)^(T) ⊗P_(R)]vec(Δ_(d) ^(v)),where Ψ=[(P_(T)*)^(T)⊗P_(R)] is the sparsifying dictionary and vec(Δ_(d)^(v)) is the sparse representation of the channel. Since the receivernetwork node 602 knows the sparsifying dictionary and the sparserepresentation of the channel, the receiver network node 602 maydetermine an estimate of the channel.

To determine the at least one AoD, the receiver network node 602 maydetermine an input-output relationship, per-tap, for the i^(th) Rx- andTx-beamformed measurements, in terms of the output signal, y_(d) _(i) ,which has dimensions 2×2:y _(d) _(i) =A _(i) H _(d) B _(i)=[(B _(i))^(T) ⊗A _(i)]vec(H_(d))=Φ_(i)Ψ vec(Δ_(d) ^(v)),where Φ_(i) is the function of Tx and Rx analog beamforming matricesused for the i^(th) measurement and Ψ is the sparsifying dictionary, asindicated above. As explained above in connection with FIG. 5 , thereceiver network node 602 may obtain beam measurements (e.g., RSRPmeasurements) associated with a plurality of beam pairs.

In some aspects, the receiver network node 602 may select beam pairs(e.g., each pair including a Tx beam and an Rx beam) in a manner thatfacilitates reconstructing H channels (e.g., having a dimension of 8×64)using 2×2 AHB measurements. To select the beam pairs, the receivernetwork node 602 may rank the obtained RSRP measurements of the beampairs from highest to lowest. The receiver network node 602 may selectthe top M beam pairs providing M number of 2×2 AHB measurements. Usingthe selected M beam pairs, the receiver network node 602 may compute theKronecker product to obtain the matrix Φ.

In some aspects, for each beam pair, the receiver network node 602 maydetermine a dth delay tap of the channel impulse response (CIR) for theith Tx beam and the ith Rx beam (A_(i),B_(i)). Additionally, forexample, the receiver network node 602 may determine a second CIR forthe dth delay tap associated with a second beam pair (A_(j),B_(j)).Stacking these two CIRs yields

$y_{d} = {\begin{bmatrix}y_{d,i} \\y_{d,j}\end{bmatrix}.}$Thus, stacking all M of the CIR measurements yields a standard sparserecovery formulation:

${y_{d} = {\begin{bmatrix}y_{d_{1}} \\y_{d_{2}} \\ \vdots \\y_{d_{M}}\end{bmatrix} = {{\begin{bmatrix}\Phi_{1} \\\Phi_{2} \\ \vdots \\\Phi_{M}\end{bmatrix}{{\Psi{ve}c}\left( \Delta_{d}^{v} \right)}} = {{{{\Phi\Psi}{vec}}\left( \Delta_{d}^{v} \right)} = {{\Phi\Psi}x_{d}}}}}},$and given y_(d) and the measurement matrix ΦΨ, the receiver network node602 may use a sparse recovery procedure to recover x_(d) and henceH_(d). In some aspects, the receiver network node 602 may use any numberof different sparse recovery procedures. For example, in some aspects,the receiver network node 602 may use an orthogonal matching pursuitprocedure for sparse recovery, hard thresholding, iterative hardthresholding, and/or iterative soft thresholding, among other examples.

Millimeter wave channels are sparse in the angular domain. Forcompressed sensing-based methods (such as OMP), this domain knowledgeabout millimeter wave channels may be leveraged in designing thesparsifying dictionaries. For example, based at least in part on thesparsity of millimeter wave channels in the angular domain, the angularspace at the transmitter and receiver sides may be divided into 2-Dgrids and the wireless channel may be represented in the angular domain.Accordingly, the complexity of the compressed sensing-based approach maybe high due to the resulting high resolution for the 2-D angular grid.

To reduce the complexity associated with compressed sensing-basedmethods, some aspects may utilize dictionary learning. Using dictionarylearning, the receiver network node 602 may directly learn thesparsifying dictionary from training data, rather than relying on are-defined sparsifying dictionary as is the case in compressedsensing-based methods. In other words, the network node 602 may learnthe basis over which the wireless channel is sparse directly fromchannel data which may give result in a lower dimensionality for thesparsifying dictionary. A lower dimensionality for the sparsifyingdictionary may lead to lower complexity, compared to compressedsensing-based methods, without compromising performance.

As indicated above, FIGS. 6A and 6B are provided as an example. Otherexamples may differ from what is described with regard to FIGS. 6A and6B.

FIG. 7 is a flow chart illustrating an example 700 of an orthogonalmatching pursuit (OMP) procedure that may be used to determine apredicted AoD, in accordance with the present disclosure. In someaspects, for example, the OMP procedure may be performed by a receivernetwork node (e.g., the receiver network node 602 depicted in FIGS. 6Aand 6B).

In some aspects, the receiver network node may determine, using theprocedures described above in connection with FIGS. 6A and 6B, y_(d) andthe measurement matrix ΦΨ. The OMP procedure illustrated in FIG. 7 maybe used to recover x_(d) and hence H_(d). The OMP procedure is asuccessive interference cancelling-based mechanism. In some aspects, theOMP procedure may be performed per-tap. The example 700 illustrates theOMP procedure for tap d. In some aspects, the receiver network node mayleverage the sparsity of the mmW channel in the tap domain so that theOMP procedure only needs to be run for a few dominant taps. For eachtap, each iteration of the OMP procedure identifies the most likely AoAand AoD. Through the iterative process, the contribution of theidentified angles is subtracted from the observation vector, and theresidual is computed. In some aspects, the OMP procedure may be iteratedup to a point at which a specified criterion is satisfied (e.g., themean squared error (MSE) of the residual is less than a threshold) oruntil a specified number of iterations have been completed.

As shown by reference number 705, the receiver network node provides, asinput to the OMP procedure that includes y_(d), Φ, and Ψ. As shown byreference number 710, the receiver network node initializes

=Ø,

=Ø, and y′_(d)=y_(d). As shown by reference number 715, the receivernetwork node sets {circumflex over (Ψ)}=Ψ. Then, as shown by referencenumber 720, the receiver network node performs a correlation step, inwhich the receiver network node computes the Hermitian of Φ{circumflexover (Ψ)} and multiply it by the observation matrix:{circumflex over (ι)}=argmax_(i)|(Φ{circumflex over (Ψ)})*y′ _(d)|,where the i^(th) index corresponds to an AoA and AoD quadruple from thesparsifying dictionary. In some aspects, the step indicated by referencenumber 720 may be conceptualized as a matching step. For example, inthis step, the receiver network node correlates the sensing matrix withthe observation matrix. Each of the columns of the Φ{circumflex over(Ψ)} matrix provides one of the pairs of AoA and AoD (in both azimuthand elevation). The argmax_(i) operator is used to determine the columnfrom the Φ{circumflex over (Ψ)} matrix that has the maximum observation,which enables extraction of the angles AoA and AoD in the next step.

As shown by reference number 725, the receiver network node thenextracts, based on the maximum observation determined above, the anglesAoA_({circumflex over (ι)}), ZoA_({circumflex over (ι)}),AoD_({circumflex over (ι)}), and ZoD_({circumflex over (ι)}) bydetermining:

=[

a _(R)(AoA _({circumflex over (ι)}) ,ZoA _({circumflex over (ι)}))], and

=[

a _(T)(AoD _({circumflex over (ι)}) ,ZoD _({circumflex over (ι)}))],where a_(R)(AoA_({circumflex over (ι)}),ZoA_({circumflex over (ι)})) isthe transmitter network node antenna element response vector anda_(T)(AoD_({circumflex over (ι)}),ZoD_({circumflex over (ι)})) is thereceiver network node response vector, and where, for the purpose ofthis mathematical expression, “AoA” refers to azimuth angle of arrival,“ZoA” refers to zenith angle of arrival, “AoD” refers to azimuth angleof departure, and “ZoD” refers to zenith angle of departure. The stepalso includes computing:{circumflex over (Ψ)}=[(

)^(T)⊗

].

As shown by reference number 730, the receiver network node computes aresidual, subtracting out the strongest cluster:y′ _(d) =y _(d)−Φ{circumflex over (Ψ)}

,where

=(Φ{circumflex over (Ψ)})*y_(d). As shown, the receiver network noderepeats the steps identified by reference numbers 715, 720, 725, and730. For example, for the second iteration, the receiver network nodeextracts the angles based on the second strongest cluster and, for thethird iteration, the receiver network node extracts the angles based onthe third strongest cluster. As shown by reference number 735, the OMPprocedure produces the output: {circumflex over (Ψ)},

, which includes a channel estimate. In some aspects, the OMP proceduremay be used to determine the strongest cluster only, in which case theprocedure may need to be performed only once (one iteration). Forexample, in indoor hotspot (InH) deployments, where there are often manyline-of-sight (LoS) channel clusters, the OMP may be used to identifythe LoS, which typically will be the best cluster to use forcommunication.

As indicated above, FIG. 7 is provided as an example. Other examples maydiffer from what is described with regard to FIG. 7 .

FIGS. 8A and 8B are diagram illustrating examples 800 and 805 associatedwith beam selection, in accordance with the present disclosure. Theexample 800 depicts an exemplary graphical representation of atransmitter network node beamforming codebook and the example 805depicts an exemplary graphical representation of a receiver network nodebeamforming codebook.

As shown in FIG. 8A, the graphical representation of the receivernetwork node codebook is depicted using a two dimensional graph having ahorizontal axis that corresponds to azimuth ϕ_(t) and a vertical axisthat corresponds to elevation θ_(t). As shown, the receiver network nodecodebook includes beams 810, 815, 820, and 825 (represented as dotsindicating directions as defined by the associated angles) arrangedaccording to azimuth and elevation such that, in this example, there aretwo azimuth values and two elevation values corresponding to the beams810, 815, 820, and 825, thereby defining a total of four beams 810, 815,820, and 825. The true channel is indicated by the direction 830 (asshown by a larger dot among a group of small dots). The smaller dotsindicate rays associated with the true channel direction 830.

As shown in FIG. 8A, the receiver network node, using one or more of theoperations described above in connection with FIGS. 5-6B, may determinepredicted AoAs 835, 840, 845, and 850. The AoA 850 also corresponds tothe predicted best AoA, which also is a representation of the estimatedchannel direction that may be determined using the sparse recoverydirection. If the receiver network node uses codebook beamforming, theselected beam, from the beamforming codebook, may be the beam 820.However, in some aspects, the receiver network node may direct a custombeam to the direction of the AoA 850. As shown, the custom beam is,therefore, much closer in direction to the direction of the true channeldirection 830 than is the direction of the codebook beam 820.Additionally, the receiver network node may, as described above,transmit an AoD report to the transmitter network node that informs thetransmitter network node of a corresponding predicted AoD, allowing thetransmitter network node to also form a custom beam in the direction ofthe estimated channel. In this way, some aspects of the presentdisclosure may facilitate selection of, and communication with, beampairs that provide a higher quality signal.

As shown in FIG. 8B, the graphical representation of the transmitternetwork node codebook is depicted using a two dimensional graph having ahorizontal axis that corresponds to azimuth ϕ_(t) and a vertical axisthat corresponds to elevation θ_(t). As shown, the transmitter networknode codebook includes beams 855 (represented as dots indicatingdirections as defined by the associated angles) arranged according toazimuth and elevation such that, in this example, there are eightazimuth values and four elevation values corresponding to the beams 855,thereby defining a total of 32 beams 855. The true channel is indicatedby the direction 860.

In some aspects, as indicated above, the receiver network node mayindicate a predicted AoD direction 865 to the transmitter network node.The transmitter network node may generate a custom beam in the predictedAoD direction 865 to facilitate communication with the receiver networknode. In some aspects, the transmitter network node may determine thatthe codebook beam 870 is as close to, or closer to, the true channeldirection 860. In this case, the transmitter network node may decide touse the codebook beam 870 rather than the custom beam. The transmitternetwork node may indicate to the receiver network node whether thecustom beam or the codebook beam will be used.

As indicated above, FIGS. 8A and 8B are provided as examples. Otherexamples may differ from what is described with regard to FIGS. 8A and8B.

FIG. 9 is a diagram illustrating an example process 900 performed, forexample, by a first network node, in accordance with the presentdisclosure. Example process 900 is an example where the first networknode (e.g., receiver network node 505) performs operations associatedwith predicting AoDs. Process 900 may include aspects, such as anysingle aspect or any combination of aspects described below and/or inconnection with one or more other processes described elsewhere herein.

As shown in FIG. 9 , in some aspects, process 900 may include receivingan AoD report configuration (block 910). For example, the first networknode (e.g., using communication manager 1108 and/or reception component1102, depicted in FIG. 11 ) may receive an AoD report configuration, asdescribed above. In some aspects, the AoD report configuration indicatesa format of the AoD report.

As further shown in FIG. 9 , in some aspects, process 900 may includereceiving a signal (block 920). For example, the first network node(e.g., using communication manager 1108 and/or reception component 1102,depicted in FIG. 11 ) may receive a signal, as described above.

As further shown in FIG. 9 , in some aspects, process 900 may includeobtaining a beam measurement (block 930). For example, the first networknode (e.g., using communication manager 1108 and/or reception component1102, depicted in FIG. 11 ) may obtain a beam measurement, as describedabove. In some aspects, the beam measurement is associated with thetransmission beam based at least in part on at least one reception beamused to receive the signal.

In some aspects, the beam measurement is associated with at least onebeam pair, of a set of beam pairs, corresponding to a subset of RSRPmeasurements having largest RSRP values of a set of RSRP valuesassociated with a plurality of beam pairs, wherein each beam pair of theplurality of beam pairs comprises a transmission beam of the pluralityof transmission beams and a reception beam of the at least one receptionbeam.

As further shown in FIG. 9 , in some aspects, process 900 may includedetermining at least one predicted AoD (block 940). For example, thefirst network node (e.g., using communication manager 1108 and/ordetermination component 1110, depicted in FIG. 11 ) may determine atleast one predicted AoD, as described above. In some aspects, the firstnetwork node may determine the at least one predicted AoD based at leastin part on performing a sparse recovery operation using the beammeasurement as an input to the sparse recovery operation.

In some aspects, the at least one predicted AoD is based at least inpart on a sparse recovery operation. In some aspects, the sparserecovery operation comprises a machine learning operation. In someaspects, the sparse recovery operation comprises a compressed sensingoperation. In some aspects, the predicted AoD comprises at least one ofa predicted azimuth AoD or a predicted elevation AoD.

As further shown in FIG. 9 , in some aspects, process 900 may includetransmitting an AoD report (block 950). For example, the first networknode (e.g., using communication manager 1108 and/or transmissioncomponent 1104, depicted in FIG. 11 ) may transmit an AoD report, asdescribed above. In some aspects, the AoD report indicates at least onepredicted AoD associated with a dominant channel cluster, wherein the atleast one predicted AoD is based at least in part on the signal. In someaspects, transmitting the AoD report comprises transmitting a per-pathangle of arrival (AoA) report that indicates the at least one predictedAoD.

In some aspects, the AoD report further indicates at least one estimatedchannel gain associated with the at least one predicted AoD. In someaspects, the AoD report indicates the at least one predicted AoD basedat least in part on indicating at least one quantized predicted AoD, andwherein the AoD report indicates the at least one estimated channel gainbased at least in part on indicating at least one quantized estimatedchannel gain. In some aspects, the AoD report indicates at least oneconfidence level associated with the at least one predicted AoD. In someaspects, the at least one confidence level indicates one of threevalues, the three values including a first value that indicates a lowconfidence, a second value that indicates a medium confidence, and athird value that indicates a high confidence.

As further shown in FIG. 9 , in some aspects, process 900 may includereceiving a custom indication (block 960). For example, the firstnetwork node (e.g., using communication manager 1108 and/or receptioncomponent 1102, depicted in FIG. 11 ) may receive a custom indication,as described above. In some aspects, the custom indication indicatesthat the at least one additional signal is associated with the customtransmission beam. In some aspects, the custom reception beam is basedat least in part on at least one predicted AoA associated with the atleast one predicted AoD.

As further shown in FIG. 9 , in some aspects, process 900 may includereceiving at least one additional signal (block 970). For example, thefirst network node (e.g., using communication manager 1108 and/orreception component 1102, depicted in FIG. 11 ) may receive the at leastone additional signal, as described above. In some aspects, the at leastone additional signal is associated with the predicted AoD.

In some aspects, the at least one additional signal comprises a datatransmission signal. In some aspects, the at least one additional signalis associated with a custom transmission beam corresponding to thepredicted AoD. In some aspects, the custom transmission beam is notassociated with a beamforming codebook. In some aspects, receiving theat least one additional signal comprises receiving the at least oneadditional signal using a custom reception beam based at least in parton receiving the custom indication. In some aspects, the least oneadditional signal corresponds to a custom transmission beam based atleast in part on the at least one confidence level indicating the thirdvalue.

Although FIG. 9 shows example blocks of process 900, in some aspects,process 900 may include additional blocks, fewer blocks, differentblocks, or differently arranged blocks than those depicted in FIG. 9 .Additionally, or alternatively, two or more of the blocks of process 900may be performed in parallel.

FIG. 10 is a diagram illustrating an example process 1000 performed, forexample, by a first network node, in accordance with the presentdisclosure. Example process 1000 is an example where the first networknode (e.g., transmitter network node 510) performs operations associatedwith predicting AoDs. Process 1000 may include aspects, such as anysingle aspect or any combination of aspects described below and/or inconnection with one or more other processes described elsewhere herein.

As shown in FIG. 10 , in some aspects, process 1000 may includetransmitting an AoD report configuration (block 1010). For example, thefirst network node (e.g., using communication manager 1108 and/ortransmission component 1104, depicted in FIG. 11 ) may transmit an AoDreport configuration, as described above. In some aspects, the AoDreport configuration indicates a format of an AoD report.

As further shown in FIG. 10 , in some aspects, process 1000 may includetransmitting a signal (block 1020). For example, the first network node(e.g., using communication manager 1108 and/or transmission component1104, depicted in FIG. 11 ) may transmit a signal, as described above.

In some aspects, the signal is associated with a transmission beam of aplurality of transmission beams, wherein the sparse recovery operationis based at least in part on a beam measurement associated with thetransmission beam based at least in part on at least one reception beamused to receive the signal. In some aspects, the beam measurement is aninput to the sparse recovery operation. In some aspects, the beammeasurement is associated with at least one beam pair, of a set of beampairs, corresponding to a subset of RSRP measurements having largestRSRP values of a set of RSRP values associated with a plurality of beampairs, wherein each beam pair of the plurality of beam pairs comprises atransmission beam of the plurality of transmission beams and a receptionbeam of the at least one reception beam.

As further shown in FIG. 10 , in some aspects, process 1000 may includereceiving an AoD report (block 1030). For example, the first networknode (e.g., using communication manager 1108 and/or reception component1102, depicted in FIG. 11 ) may receive an AoD report, as describedabove. In some aspects, the AoD report indicates at least one predictedAoD associated with a dominant channel cluster. In some aspects, the atleast one predicted AoD is based at least in part on the signal.

In some aspects, the at least one predicted AoD is based at least inpart on a sparse recovery operation. In some aspects, the sparserecovery operation comprises a machine learning operation. In someaspects, the sparse recovery operation comprises a compressed sensingoperation. In some aspects, the predicted AoD comprises at least one ofa predicted azimuth AoD or a predicted elevation AoD. In some aspects,receiving the AoD report comprises receiving a per-path AoA report thatindicates the at least one predicted AoD.

In some aspects, the AoD report further indicates at least one estimatedchannel gain associated with the at least one predicted AoD. In someaspects, the AoD report indicates the at least one predicted AoD basedat least in part on indicating at least one quantized predicted AoD, andwherein the AoD report indicates the at least one estimated channel gainbased at least in part on indicating at least one quantized estimatedchannel gain. In some aspects, the AoD report indicates at least oneconfidence level associated with the at least one predicted AoD. In someaspects, the at least one confidence level indicates one of threevalues, the three values including a first value that indicates a lowconfidence, a second value that indicates a medium confidence, and athird value that indicates a high confidence.

As further shown in FIG. 10 , in some aspects, process 1000 may includetransmitting a custom indication (block 1040). For example, the firstnetwork node (e.g., using communication manager 1108 and/or transmissioncomponent 1104, depicted in FIG. 11 ) may transmit a custom indication,as described above. In some aspects, the custom indication indicatesthat at least one additional signal is associated with the customtransmission beam. In some aspects, the custom transmission beam is notassociated with a beamforming codebook.

As further shown in FIG. 10 , in some aspects, process 1000 may includetransmitting at least one additional signal (block 1050). For example,the first network node (e.g., using communication manager 1108 and/ortransmission component 1104, depicted in FIG. 11 ) may transmit at leastone additional signal, as described above. In some aspects, the at leastone additional signal is associated with the predicted AoD.

In some aspects, the at least one additional signal comprises a datatransmission signal. In some aspects, the at least one additional signalis associated with a custom transmission beam corresponding to thepredicted AoD. In some aspects, the at least one additional signal isassociated with a custom reception beam based at least in part on thecustom indication. In some aspects, the custom reception beam is basedat least in part on at least one predicted AoA associated with the atleast one predicted AoD. In some aspects, the at least one additionalsignal corresponds to a custom transmission beam based at least in parton the at least one confidence level indicating the third value.

Although FIG. 10 shows example blocks of process 1000, in some aspects,process 1000 may include additional blocks, fewer blocks, differentblocks, or differently arranged blocks than those depicted in FIG. 10 .Additionally, or alternatively, two or more of the blocks of process1000 may be performed in parallel.

FIG. 11 is a diagram of an example apparatus 1100 for wirelesscommunication. The apparatus 1100 may be, or include, a network node, ora network node may include the apparatus 1100. In some aspects, theapparatus 1100 includes a reception component 1102 and a transmissioncomponent 1104, which may be in communication with one another (forexample, via one or more buses and/or one or more other components). Asshown, the apparatus 1100 may communicate with another apparatus 1106(such as a UE, a base station, or another wireless communication device)using the reception component 1102 and the transmission component 1104.As further shown, the apparatus 1100 may include the communicationmanager 1108. The communication manager 1108 may include a determinationcomponent 1110.

In some aspects, the apparatus 1100 may be configured to perform one ormore operations described herein in connection with FIGS. 5, 6A, 6B, 7,8A, and 8B. Additionally, or alternatively, the apparatus 1100 may beconfigured to perform one or more processes described herein, such asprocess 900 of FIG. 9 , process 1000 of FIG. 10 , or a combinationthereof. In some aspects, the apparatus 1100 and/or one or morecomponents shown in FIG. 11 may include one or more components of the UEor the base station described in connection with FIG. 2 . Additionally,or alternatively, one or more components shown in FIG. 11 may beimplemented within one or more components described in connection withFIG. 2 . Additionally, or alternatively, one or more components of theset of components may be implemented at least in part as software storedin a memory. For example, a component (or a portion of a component) maybe implemented as instructions or code stored in a non-transitorycomputer-readable medium and executable by a controller or a processorto perform the functions or operations of the component.

The reception component 1102 may receive communications, such asreference signals, control information, data communications, or acombination thereof, from the apparatus 1106. The reception component1102 may provide received communications to one or more other componentsof the apparatus 1100. In some aspects, the reception component 1102 mayperform signal processing on the received communications (such asfiltering, amplification, demodulation, analog-to-digital conversion,demultiplexing, deinterleaving, de-mapping, equalization, interferencecancellation, or decoding, among other examples), and may provide theprocessed signals to the one or more other components of the apparatus1100. In some aspects, the reception component 1102 may include one ormore antennas, a modem, a demodulator, a MIMO detector, a receiveprocessor, a controller/processor, a memory, or a combination thereof,of the UE or the base station described in connection with FIG. 2 .

The transmission component 1104 may transmit communications, such asreference signals, control information, data communications, or acombination thereof, to the apparatus 1106. In some aspects, one or moreother components of the apparatus 1100 may generate communications andmay provide the generated communications to the transmission component1104 for transmission to the apparatus 1106. In some aspects, thetransmission component 1104 may perform signal processing on thegenerated communications (such as filtering, amplification, modulation,digital-to-analog conversion, multiplexing, interleaving, mapping, orencoding, among other examples), and may transmit the processed signalsto the apparatus 1106. In some aspects, the transmission component 1104may include one or more antennas, a modem, a modulator, a transmit MIMOprocessor, a transmit processor, a controller/processor, a memory, or acombination thereof, of the UE or the base station described inconnection with FIG. 2 . In some aspects, the transmission component1104 may be co-located with the reception component 1102 in atransceiver.

The reception component 1102 may receive a signal. The transmissioncomponent 1104 may transmit an AoD report that indicates at least onepredicted AoD associated with a dominant channel cluster, wherein the atleast one predicted AoD is based at least in part on the signal.

The communication manager 1108 and/or the determination component 1110may determine the at least one predicted AoD based at least in part onperforming the sparse recovery operation using the beam measurement asan input to the sparse recovery operation. In some aspects, thecommunication manager 1108 may include one or more antennas, a modem, acontroller/processor, a memory, or a combination thereof, of the UE orthe base station described in connection with FIG. 2 . In some aspects,the communication manager 1108 may be, be similar to, include, or beincluded in, the communication manager 140 or the communication manager150, depicted in FIGS. 1 and 2 . In some aspects, the communicationmanager 1108 may include the reception component 1102 and/or thetransmission component 1104. In some aspects, the determinationcomponent 1110 may include one or more antennas, a modem, acontroller/processor, a memory, or a combination thereof, of the UE orthe base station described in connection with FIG. 2 . In some aspects,the determination component 1110 may include the reception component1102 and/or the transmission component 1104.

The reception component 1102 may receive at least one additional signalassociated with the predicted AoD. The reception component 1102 mayreceive a custom indication that indicates that the at least oneadditional signal is associated with the custom transmission beam. Thereception component 1102 may receive a codebook indication thatindicates that the at least one additional signal is associated with acodebook beam based at least in part on the predicted AoD being within athreshold angle of the codebook beam. The reception component 1102 mayreceive an AoD report configuration that indicates a format of the AoDreport. The reception component 1102 may receive at least one additionalsignal associated with the predicted AoD and corresponding to a customtransmission beam based at least in part on the at least one confidencelevel indicating the third value.

The transmission component 1104 may transmit a signal. The receptioncomponent 1102 may receive an AoD report that indicates at least onepredicted AoD associated with a dominant channel cluster, wherein the atleast one predicted AoD is based at least in part on the signal. Thetransmission component 1104 may transmit at least one additional signalassociated with the predicted AoD. The transmission component 1104 maytransmit an AoD report configuration that indicates a format of the AoDreport.

The transmission component 1104 may transmit a custom indication thatindicates that the at least one additional signal is associated with thecustom transmission beam. The transmission component 1104 may transmit acodebook indication that indicates that the at least one additionalsignal is associated with a codebook beam based at least in part on thepredicted AoD being within a threshold angle of the codebook beam. Thetransmission component 1104 may transmit at least one additional signalassociated with the predicted AoD and corresponding to a customtransmission beam based at least in part on the at least one confidencelevel indicating the third value.

The number and arrangement of components shown in FIG. 11 are providedas an example. In practice, there may be additional components, fewercomponents, different components, or differently arranged componentsthan those shown in FIG. 11 . Furthermore, two or more components shownin FIG. 11 may be implemented within a single component, or a singlecomponent shown in FIG. 11 may be implemented as multiple, distributedcomponents. Additionally, or alternatively, a set of (one or more)components shown in FIG. 11 may perform one or more functions describedas being performed by another set of components shown in FIG. 11 .

FIG. 12 is a diagram illustrating an example 1200 of a hardwareimplementation for an apparatus 1202 employing a processing system 1204.The apparatus 1202 may be, be similar to, include, or be included in theapparatus 1100 shown in FIG. 11 . For example, the apparatus 1202 maybe, include, or be included in, a network node.

The processing system 1204 may be implemented with a bus architecture,represented generally by the bus 1206. The bus 1206 may include anynumber of interconnecting buses and bridges depending on the specificapplication of the processing system 1204 and the overall designconstraints. The bus 1206 links together various circuits including oneor more processors and/or hardware components, represented by aprocessor 1208, the illustrated components, and the computer-readablemedium/memory 1210. The bus 1206 may also link various other circuits,such as timing sources, peripherals, voltage regulators, powermanagement circuits, and/or the like.

The processing system 1204 may be coupled to and/or associated with atransceiver 1212. The transceiver 1212 is coupled to one or moreantennas 1214. The transceiver 1212 provides a means for communicatingwith various other apparatuses over a transmission medium. Thetransceiver 1212 receives a signal from the one or more antennas 1214,extracts information from the received signal, and provides theextracted information to the processing system 1204, specifically areception component 1216. The reception component 1216 may be, besimilar to, include, or be included in, the reception component 1102,depicted in FIG. 11 . In addition, the transceiver 1212 receivesinformation from the processing system 1204, specifically a transmissioncomponent 1218, and generates a signal to be applied to the one or moreantennas 1214 based at least in part on the received information. Thetransmission component 1218 may be, be similar to, include, or beincluded in, the transmission component 1104, depicted in FIG. 11 .

The processor 1208 is coupled to the computer-readable medium/memory1210. The processor 1208 is responsible for general processing,including the execution of software stored on the computer-readablemedium/memory 1210. The software, when executed by the processor 1208,causes the processing system 1204 to perform the various functionsdescribed herein in connection with a receiving device. Thecomputer-readable medium/memory 1210 may also be used for storing datathat is manipulated by the processor 1208 when executing software. Theprocessing system also may include a communication manager 1220. Thecommunication manager 1220 may organize, prioritize, activate,facilitate and/or otherwise manage communication operations performed bythe apparatus 1202. The processing system 1204 may include any number ofadditional components not illustrated in FIG. 12 . The componentsillustrated and/or not illustrated may be software modules running inthe processor 1208, resident/stored in the computer-readablemedium/memory 1210, one or more hardware modules coupled to theprocessor 1208, or some combination thereof.

In some aspects, the processing system 1204 may be a component of thebase station 110 and may include the memory 242 and/or at least one ofthe TX MIMO processor 230, the receive processor 238, and/or thecontroller/processor 240. In some aspects, the processing system 1204may be a component of the UE 120 and may include the memory 282 and/orat least one of the TX MIMO processor 266, the receive processor 258,and/or the controller/processor 280. In some aspects, the apparatus 1202for wireless communication provides means for receiving a signal andtransmitting an AoD report that indicates at least one predicted AoDassociated with a dominant channel cluster, wherein the at least onepredicted AoD is based at least in part on the signal.

In some aspects, the apparatus 1202 for wireless communication providesmeans for obtaining a beam measurement associated with the transmissionbeam based at least in part on at least one reception beam used toreceive the signal. In some aspects, the apparatus 1202 for wirelesscommunication provides means for obtaining a beam measurement associatedwith the transmission beam based at least in part on at least onereception beam used to receive the signal. In some aspects, theapparatus 1202 for wireless communication provides means for determiningthe at least one predicted AoD based at least in part on performing thesparse recovery operation using the beam measurement as an input to thesparse recovery operation.

In some aspects, the apparatus 1202 for wireless communication providesmeans for receiving at least one additional downlink signal associatedwith the predicted AoD. In some aspects, the apparatus 1202 for wirelesscommunication provides means for receiving a custom indication thatindicates that the at least one additional downlink signal is associatedwith the custom transmission beam. In some aspects, the apparatus 1202for wireless communication provides means for receiving the at least oneadditional downlink signal using a custom reception beam based at leastin part on receiving the custom indication. In some aspects, theapparatus 1202 for wireless communication provides means for receiving acodebook indication that indicates that the at least one additionaldownlink signal is associated with a codebook beam based at least inpart on the predicted AoD being within a threshold angle of the codebookbeam.

In some aspects, the apparatus 1202 for wireless communication providesmeans for receiving an AoD report configuration that indicates a formatof the AoD report. In some aspects, the apparatus 1202 for wirelesscommunication provides means for receiving at least one additionaldownlink signal associated with the predicted AoD and corresponding to acustom transmission beam based at least in part on the at least oneconfidence level indicating the third value.

In some aspects, the apparatus 1202 for wireless communication providesmeans for transmitting a signal and receiving an AoD report thatindicates at least one predicted AoD associated with a dominant channelcluster, wherein the at least one predicted AoD is based at least inpart on the signal. In some aspects, the apparatus 1202 for wirelesscommunication provides means for transmitting at least one additionaldownlink signal associated with the predicted AoD. In some aspects, theapparatus 1202 for wireless communication provides means fortransmitting a custom indication that indicates that the at least oneadditional downlink signal is associated with the custom transmissionbeam.

In some aspects, the apparatus 1202 for wireless communication providesmeans for transmitting a codebook indication that indicates that the atleast one additional downlink signal is associated with a codebook beambased at least in part on the predicted AoD being within a thresholdangle of the codebook beam. In some aspects, the apparatus 1202 forwireless communication provides means for transmitting an AoD reportconfiguration that indicates a format of the AoD report. In someaspects, the apparatus 1202 for wireless communication provides meansfor transmitting at least one additional downlink signal associated withthe predicted AoD and corresponding to a custom transmission beam basedat least in part on the at least one confidence level indicating thethird value.

The aforementioned means may be one or more of the aforementionedcomponents of the processing system 1204 of the apparatus 1202configured to perform the functions recited by the aforementioned means.As described elsewhere herein, the processing system 1204 may includethe TX MIMO processor 230 or 266, the receive processor 238 or 258, thecontroller/processor 240 or 280, and/or the memory 242 or 282. In oneconfiguration, the aforementioned means may be the TX MIMO processor 230or 266, the receive processor 238 or 258, the controller/processor 240or 280, and/or the memory 242 or 282 configured to perform the functionsand/or operations recited herein.

FIG. 12 is provided as an example. Other examples may differ from whatis described in connection with FIG. 12 .

FIG. 13 is a diagram illustrating an example 1300 of an implementationof code and circuitry for an apparatus 1302 for wireless communication.The apparatus 1302 may be, be similar to, include, or be included in theapparatus 1100 shown in FIG. 11 , and/or the apparatus 1202 shown inFIG. 12 . For example, the apparatus 1302 may be, include, or beincluded in, a network node (e.g., UE or a base station). The apparatus1302 may include a processing system 1304, which may include a bus 1306coupling one or more components such as, for example, a processor 1308,computer-readable medium/memory 1310, a transceiver 1312, and/or thelike. As shown, the transceiver 1312 may be coupled to one or moreantennas 1314.

As further shown in FIG. 13 , the apparatus 1302 may include circuitryfor receiving a signal (circuitry 1316). For example, the apparatus 1302may include circuitry 1316 to enable the apparatus 1302 to receive asignal.

As further shown in FIG. 13 , the apparatus 1302 may include circuitryfor transmitting an AoD report that indicates at least one predicted AoDassociated with a dominant channel cluster, wherein the at least onepredicted AoD is based at least in part on the signal (circuitry 1318).For example, the apparatus 1302 may include circuitry 1318 to enable theapparatus 1302 to transmit an AoD report that indicates at least onepredicted AoD associated with a dominant channel cluster, wherein the atleast one predicted AoD is based at least in part on the signal.

As further shown in FIG. 13 , the apparatus 1302 may include, stored incomputer-readable medium 1310, code for receiving a signal (code 1320).For example, the apparatus 1302 may include code 1320 that, whenexecuted by the processor 1308, may cause the transceiver 1312 toreceive a signal.

As further shown in FIG. 13 , the apparatus 1302 may include, stored incomputer-readable medium 1310, code for transmitting an AoD report thatindicates at least one predicted AoD associated with a dominant channelcluster, wherein the at least one predicted AoD is based at least inpart on the signal (code 1322). For example, the apparatus 1302 mayinclude code 1322 that, when executed by the processor 1308, may causethe transceiver 1312 to transmit an AoD report that indicates at leastone predicted AoD associated with a dominant channel cluster, whereinthe at least one predicted AoD is based at least in part on the signal.

As further shown in FIG. 13 , the apparatus 1302 may include circuitryfor transmitting a signal (circuitry 1324). For example, the apparatus1302 may include circuitry 1316 to enable the apparatus 1302 to transmita signal.

As further shown in FIG. 13 , the apparatus 1302 may include circuitryfor receiving an AoD report that indicates at least one predicted AoDassociated with a dominant channel cluster, wherein the at least onepredicted AoD is based at least in part on the signal (circuitry 1326).For example, the apparatus 1302 may include circuitry 1318 to enable theapparatus 1302 to receive an AoD report that indicates at least onepredicted AoD associated with a dominant channel cluster, wherein the atleast one predicted AoD is based at least in part on the signal.

As further shown in FIG. 13 , the apparatus 1302 may include, stored incomputer-readable medium 1310, code for transmitting a signal (code1328). For example, the apparatus 1302 may include code 1320 that, whenexecuted by the processor 1308, may cause the transceiver 1312 totransmit a signal.

As further shown in FIG. 13 , the apparatus 1302 may include, stored incomputer-readable medium 1310, code for receiving an AoD report thatindicates at least one predicted AoD associated with a dominant channelcluster, wherein the at least one predicted AoD is based at least inpart on the signal (code 1330). For example, the apparatus 1302 mayinclude code 1322 that, when executed by the processor 1308, may causethe transceiver 1312 to receive an AoD report that indicates at leastone predicted AoD associated with a dominant channel cluster, whereinthe at least one predicted AoD is based at least in part on the signal.

FIG. 13 is provided as an example. Other examples may differ from whatis described in connection with FIG. 13 .

The following provides an overview of some Aspects of the presentdisclosure:

-   -   Aspect 1: A method of wireless communication performed by a        first network node comprising: receiving a signal; and        transmitting an angle of departure (AoD) report that indicates        at least one predicted AoD associated with a dominant channel        cluster, wherein the at least one predicted AoD is based at        least in part on the signal.    -   Aspect 2: The method of Aspect 1, wherein the at least one        predicted AoD is based at least in part on a sparse recovery        operation.    -   Aspect 3: The method of Aspect 2, wherein the sparse recovery        operation comprises a machine learning operation.    -   Aspect 4: The method of Aspect 2, wherein the sparse recovery        operation comprises a compressed sensing operation.    -   Aspect 5: The method of any of Aspects 2-4, wherein the signal        is associated with a transmission beam of a plurality of        transmission beams, the method further comprising obtaining a        beam measurement associated with the transmission beam based at        least in part on at least one reception beam used to receive the        signal.    -   Aspect 6: The method of Aspect 5, further comprising determining        the at least one predicted AoD based at least in part on        performing the sparse recovery operation using the beam        measurement as an input to the sparse recovery operation.    -   Aspect 7: The method of Aspect 6, wherein the beam measurement        is associated with at least one beam pair, of a set of beam        pairs, corresponding to a subset of reference signal received        power (RSRP) measurements having largest RSRP values of a set of        RSRP values associated with a plurality of beam pairs, wherein        each beam pair of the plurality of beam pairs comprises a        transmission beam of the plurality of transmission beams and a        reception beam of the at least one reception beam.    -   Aspect 8: The method of any of Aspects 1-7, wherein the        predicted AoD comprises at least one of a predicted azimuth AoD        or a predicted elevation AoD.    -   Aspect 9: The method of any of Aspects 1-8, wherein transmitting        the AoD report comprises transmitting a per-path angle of        arrival (AoA) report that indicates the at least one predicted        AoD.    -   Aspect 10: The method of any of Aspects 1-9, further comprising        receiving at least one additional signal associated with the        predicted AoD.    -   Aspect 11: The method of Aspect 10, wherein the at least one        additional signal comprises a data transmission signal.    -   Aspect 12: The method of either of Aspects 10 or 11, wherein the        at least one additional signal is associated with a custom        transmission beam corresponding to the predicted AoD.    -   Aspect 13: The method of Aspect 12, wherein the custom        transmission beam is not associated with a beamforming codebook.    -   Aspect 14: The method of either of Aspects 12 or 13, further        comprising receiving a custom indication that indicates that the        at least one additional signal is associated with the custom        transmission beam.    -   Aspect 15: The method of Aspect 14, wherein receiving the at        least one additional signal comprises receiving the at least one        additional signal using a custom reception beam based at least        in part on receiving the custom indication.    -   Aspect 16: The method of Aspect 15, wherein the custom reception        beam is based at least in part on at least one predicted angle        of arrival (AoA) associated with the at least one predicted AoD.    -   Aspect 17: The method of any of Aspects 10-16, further        comprising receiving a codebook indication that indicates that        the at least one additional signal is associated with a codebook        beam based at least in part on the predicted AoD being within a        threshold angle of the codebook beam.    -   Aspect 18: The method of any of Aspects 1-17, wherein the AoD        report further indicates at least one estimated channel gain        associated with the at least one predicted AoD.    -   Aspect 19: The method of Aspect 18, wherein the AoD report        indicates the at least one predicted AoD based at least in part        on indicating at least one quantized predicted AoD, and wherein        the AoD report indicates the at least one estimated channel gain        based at least in part on indicating at least one quantized        estimated channel gain.    -   Aspect 20: The method of any of Aspects 1-19, further comprising        receiving an AoD report configuration that indicates a format of        the AoD report.    -   Aspect 21: The method of any of Aspects 1-20, wherein the AoD        report indicates at least one confidence level associated with        the at least one predicted AoD.    -   Aspect 22: The method of Aspect 21, wherein the at least one        confidence level indicates one of three values, the three values        including a first value that indicates a low confidence, a        second value that indicates a medium confidence, and a third        value that indicates a high confidence.    -   Aspect 23: The method of Aspect 22, further comprising receiving        at least one additional signal associated with the predicted AoD        and corresponding to a custom transmission beam based at least        in part on the at least one confidence level indicating the        third value.    -   Aspect 24: A method of wireless communication performed by a        first network node, comprising: transmitting a signal; and        receiving an angle of departure (AoD) report that indicates at        least one predicted AoD associated with a dominant channel        cluster, wherein the at least one predicted AoD is based at        least in part on the signal.    -   Aspect 25: The method of Aspect 24, wherein the at least one        predicted AoD is based at least in part on a sparse recovery        operation.    -   Aspect 26: The method of Aspect 25, wherein the sparse recovery        operation comprises a machine learning operation.    -   Aspect 27: The method of Aspect 25, wherein the sparse recovery        operation comprises a compressed sensing operation.    -   Aspect 28: The method of any of Aspects 25-27, wherein the        signal is associated with a transmission beam of a plurality of        transmission beams, wherein the sparse recovery operation is        based at least in part on a beam measurement associated with the        transmission beam based at least in part on at least one        reception beam used to receive the signal.    -   Aspect 29: The method of Aspect 28, wherein the beam measurement        is an input to the sparse recovery operation.    -   Aspect 30: The method of Aspect 29, wherein the beam measurement        is associated with at least one beam pair, of a set of beam        pairs, corresponding to a subset of reference signal received        power (RSRP) measurements having largest RSRP values of a set of        RSRP values associated with a plurality of beam pairs, wherein        each beam pair of the plurality of beam pairs comprises a        transmission beam of the plurality of transmission beams and a        reception beam of the at least one reception beam.    -   Aspect 31: The method of any of Aspects 24-30, wherein the        predicted AoD comprises at least one of a predicted azimuth AoD        or a predicted elevation AoD.    -   Aspect 32: The method of any of Aspects 24-30, wherein receiving        the AoD report comprises receiving a per-path angle of arrival        (AoA) report that indicates the at least one predicted AoD.    -   Aspect 33: The method of any of Aspects 24-30, further        comprising transmitting at least one additional signal        associated with the predicted AoD.    -   Aspect 34: The method of Aspect 33, wherein the at least one        additional signal comprises a data transmission signal.    -   Aspect 35: The method of either of Aspects 33 or 34, wherein the        at least one additional signal is associated with a custom        transmission beam corresponding to the predicted AoD.    -   Aspect 36: The method of Aspect 35, wherein the custom        transmission beam is not associated with a beamforming codebook.    -   Aspect 37: The method of either of Aspects 35 or 36, further        comprising transmitting a custom indication that indicates that        the at least one additional signal is associated with the custom        transmission beam.    -   Aspect 38: The method of Aspect 37, wherein transmitting the at        least one additional signal is associated with a custom        reception beam based at least in part on the custom indication.    -   Aspect 39: The method of Aspect 38, wherein the custom reception        beam is based at least in part on at least one predicted angle        of arrival (AoA) associated with the at least one predicted AoD.    -   Aspect 40: The method of any of Aspects 33-39, further        comprising transmitting a codebook indication that indicates        that the at least one additional signal is associated with a        codebook beam based at least in part on the predicted AoD being        within a threshold angle of the codebook beam.    -   Aspect 41: The method of any of Aspects 24-40, wherein the AoD        report further indicates at least one estimated channel gain        associated with the at least one predicted AoD.    -   Aspect 42: The method of Aspect 41, wherein the AoD report        indicates the at least one predicted AoD based at least in part        on indicating at least one quantized predicted AoD, and wherein        the AoD report indicates the at least one estimated channel gain        based at least in part on indicating at least one quantized        estimated channel gain.    -   Aspect 43: The method of any of Aspects 24-42, further        comprising transmitting an AoD report configuration that        indicates a format of the AoD report.    -   Aspect 44: The method of any of Aspects 24-43, wherein the AoD        report indicates at least one confidence level associated with        the at least one predicted AoD.    -   Aspect 45: The method of Aspect 44, wherein the at least one        confidence level indicates one of three values, the three values        including a first value that indicates a low confidence, a        second value that indicates a medium confidence, and a third        value that indicates a high confidence.    -   Aspect 46: The method of Aspect 45, further comprising        transmitting at least one additional signal associated with the        predicted AoD and corresponding to a custom transmission beam        based at least in part on the at least one confidence level        indicating the third value.    -   Aspect 47: An apparatus for wireless communication at a device,        comprising a processor; memory coupled with the processor; and        instructions stored in the memory and executable by the        processor to cause the apparatus to perform the method of one or        more of Aspects 1-23.    -   Aspect 48: A device for wireless communication, comprising a        memory and one or more processors coupled to the memory, the one        or more processors configured to perform the method of one or        more of Aspects 1-23.    -   Aspect 49: An apparatus for wireless communication, comprising        at least one means for performing the method of one or more of        Aspects 1-23.    -   Aspect 50: A non-transitory computer-readable medium storing        code for wireless communication, the code comprising        instructions executable by a processor to perform the method of        one or more of Aspects 1-23.    -   Aspect 51: A non-transitory computer-readable medium storing a        set of instructions for wireless communication, the set of        instructions comprising one or more instructions that, when        executed by one or more processors of a device, cause the device        to perform the method of one or more of Aspects 1-23.    -   Aspect 52: An apparatus for wireless communication at a device,        comprising a processor; memory coupled with the processor; and        instructions stored in the memory and executable by the        processor to cause the apparatus to perform the method of one or        more of Aspects 24-46.    -   Aspect 53: A device for wireless communication, comprising a        memory and one or more processors coupled to the memory, the one        or more processors configured to perform the method of one or        more of Aspects 24-46.    -   Aspect 54: An apparatus for wireless communication, comprising        at least one means for performing the method of one or more of        Aspects 24-46.    -   Aspect 55: A non-transitory computer-readable medium storing        code for wireless communication, the code comprising        instructions executable by a processor to perform the method of        one or more of Aspects 24-46.    -   Aspect 56: A non-transitory computer-readable medium storing a        set of instructions for wireless communication, the set of        instructions comprising one or more instructions that, when        executed by one or more processors of a device, cause the device        to perform the method of one or more of Aspects 24-46.

The foregoing disclosure provides illustration and description but isnot intended to be exhaustive or to limit the aspects to the preciseforms disclosed. Modifications and variations may be made in light ofthe above disclosure or may be acquired from practice of the aspects.

As used herein, the term “component” is intended to be broadly construedas hardware and/or a combination of hardware and software. “Software”shall be construed broadly to mean instructions, instruction sets, code,code segments, program code, programs, subprograms, software modules,applications, software applications, software packages, routines,subroutines, objects, executables, threads of execution, procedures,and/or functions, among other examples, whether referred to as software,firmware, middleware, microcode, hardware description language, orotherwise. As used herein, a “processor” is implemented in hardwareand/or a combination of hardware and software. It will be apparent thatsystems and/or methods described herein may be implemented in differentforms of hardware and/or a combination of hardware and software. Theactual specialized control hardware or software code used to implementthese systems and/or methods is not limiting of the aspects. Thus, theoperation and behavior of the systems and/or methods are describedherein without reference to specific software code, since those skilledin the art will understand that software and hardware can be designed toimplement the systems and/or methods based, at least in part, on thedescription herein.

As used herein, “satisfying a threshold” may, depending on the context,refer to a value being greater than the threshold, greater than or equalto the threshold, less than the threshold, less than or equal to thethreshold, equal to the threshold, not equal to the threshold, or thelike.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of various aspects. Many of thesefeatures may be combined in ways not specifically recited in the claimsand/or disclosed in the specification. The disclosure of various aspectsincludes each dependent claim in combination with every other claim inthe claim set. As used herein, a phrase referring to “at least one of” alist of items refers to any combination of those items, including singlemembers. As an example, “at least one of: a, b, or c” is intended tocover a, b, c, a+b, a+c, b+c, and a+b+c, as well as any combination withmultiples of the same element (e.g., a+a, a+a+a, a+a+b, a+a+c, a+b+b,a+c+c, b+b, b+b+b, b+b+c, c+c, and c+c+c, or any other ordering of a, b,and c).

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems and may be used interchangeably with “one or more.” Further, asused herein, the article “the” is intended to include one or more itemsreferenced in connection with the article “the” and may be usedinterchangeably with “the one or more.” Furthermore, as used herein, theterms “set” and “group” are intended to include one or more items andmay be used interchangeably with “one or more.” Where only one item isintended, the phrase “only one” or similar language is used. Also, asused herein, the terms “has,” “have,” “having,” or the like are intendedto be open-ended terms that do not limit an element that they modify(e.g., an element “having” A may also have B). Further, the phrase“based on” is intended to mean “based, at least in part, on” unlessexplicitly stated otherwise. Also, as used herein, the term “or” isintended to be inclusive when used in a series and may be usedinterchangeably with “and/or,” unless explicitly stated otherwise (e.g.,if used in combination with “either” or “only one of”).

What is claimed is:
 1. A first network node for wireless communication,comprising: one or more memories; and one or more processors coupled tothe one or more memories, the one or more processors configured to:receive a signal from a second network node; and transmit, to the secondnetwork node, an angle of departure (AoD) report that indicates at leastone predicted AoD that is associated with a dominant channel cluster ofthe signal received from the second network node.
 2. The first networknode of claim 1, wherein the at least one predicted AoD is based atleast in part on a sparse recovery operation.
 3. The first network nodeof claim 2, wherein the sparse recovery operation comprises a machinelearning operation.
 4. The first network node of claim 2, wherein thesparse recovery operation comprises a compressed sensing operation. 5.The first network node of claim 2, wherein the signal is associated witha transmission beam of a plurality of transmission beams, and whereinthe one or more processors are configured to obtain a beam measurementassociated with the transmission beam based at least in part on at leastone reception beam used to receive the signal.
 6. The first network nodeof claim 5, wherein the one or more processors are configured todetermine the at least one predicted AoD based at least in part onperforming the sparse recovery operation using the beam measurement asan input to the sparse recovery operation.
 7. The first network node ofclaim 6, wherein the beam measurement is associated with at least onebeam pair, of a set of beam pairs, corresponding to a subset ofreference signal received power (RSRP) measurements having largest RSRPvalues of a set of RSRP values associated with a plurality of beampairs, wherein each beam pair of the plurality of beam pairs comprises atransmission beam of the plurality of transmission beams and a receptionbeam of the at least one reception beam.
 8. The first network node ofclaim 1, wherein the predicted AoD comprises at least one of a predictedazimuth AoD or a predicted elevation AoD.
 9. The first network node ofclaim 1, further comprising a transceiver, wherein the one or moreprocessors, to transmit the AoD report, are configured to transmit, bythe transceiver, a per-path angle of arrival (AoA) report that indicatesthe at least one predicted AoD.
 10. The first network node of claim 1,wherein the one or more processors are configured to receive at leastone additional signal associated with the predicted AoD.
 11. The firstnetwork node of claim 10, wherein the at least one additional signalcomprises a data transmission signal.
 12. The first network node ofclaim 10, wherein the at least one additional signal is associated witha custom transmission beam corresponding to the predicted AoD.
 13. Thefirst network node of claim 12, wherein the custom transmission beam isnot associated with a beamforming codebook.
 14. The first network nodeof claim 12, wherein the one or more processors are configured toreceive a custom indication that indicates that the at least oneadditional signal is associated with the custom transmission beam. 15.The first network node of claim 14, wherein the one or more processors,to receive the at least one additional signal, are configured to receivethe at least one additional signal using a custom reception beam basedat least in part on receiving the custom indication.
 16. The firstnetwork node of claim 15, wherein the custom reception beam is based atleast in part on at least one predicted angle of arrival (AoA)associated with the at least one predicted AoD.
 17. The first networknode of claim 10, wherein the one or more processors are configured toreceive a codebook indication that indicates that the at least oneadditional signal is associated with a codebook beam based at least inpart on the predicted AoD being within a threshold angle of the codebookbeam.
 18. The first network node of claim 1, wherein the AoD reportfurther indicates at least one estimated channel gain associated withthe at least one predicted AoD.
 19. The first network node of claim 18,wherein the AoD report indicates the at least one predicted AoD based atleast in part on indicating at least one quantized predicted AoD, andwherein the AoD report indicates the at least one estimated channel gainbased at least in part on indicating at least one quantized estimatedchannel gain.
 20. The first network node of claim 1, wherein the one ormore processors are configured to receive an AoD report configurationthat indicates a format of the AoD report.
 21. The first network node ofclaim 1, wherein the AoD report indicates at least one confidence levelassociated with the at least one predicted AoD.
 22. The first networknode of claim 21, wherein the at least one confidence level indicatesone of three values, the three values including a first value thatindicates a low confidence value, a second value that indicates a mediumconfidence value, and a third value that indicates a high confidencevalue.
 23. The first network node of claim 22, wherein the one or moreprocessors are configured to receive at least one additional signalassociated with the predicted AoD and corresponding to a customtransmission beam based at least in part on the at least one confidencelevel indicating the third value.
 24. A first network node for wirelesscommunication, comprising: one or more memories; and one or moreprocessors coupled to the one or more memories, the one or moreprocessors configured to: transmit a signal to a second network node;and receive, from the second network node, an angle of departure (AoD)report that indicates at least one predicted AoD that is associated witha dominant channel cluster of the signal transmitted to the secondnetwork node.
 25. The first network node of claim 24, wherein the atleast one predicted AoD is based at least in part on a sparse recoveryoperation.
 26. The first network node of claim 25, further comprising atransceiver, wherein the one or more processors are configured totransmit, by the transceiver, at least one additional signal associatedwith the predicted AoD.
 27. A method of wireless communication performedat a first network node, comprising: receiving a signal from a secondnetwork node; and transmitting, to the second network node, an angle ofdeparture (AoD) report that indicates at least one predicted AoD that isassociated with a dominant channel cluster of the signal received fromthe second network node.
 28. The method of claim 27, wherein the atleast one predicted AoD is based at least in part on a sparse recoveryoperation.
 29. A method of wireless communication performed at a firstnetwork node, comprising: transmitting a signal to a second networknode; and receiving, from the second network node, an angle of departure(AoD) report that indicates at least one predicted AoD that isassociated with a dominant channel cluster of the signal transmitted tothe second network node.
 30. The method of claim 29, wherein the atleast one predicted AoD is based at least in part on a sparse recoveryoperation.